knitr::opts_chunk$set(echo = TRUE)

Explore global development with R

In this exercise, you will load a filtered gapminder dataset - with a subset of data on global development from 1952 - 2007 in increments of 5 years - to capture the period between the Second World War and the Global Financial Crisis.

Your task: Explore the data and visualise it in both static and animated ways, providing answers and solutions to 7 questions/tasks within this script.

Get the necessary packages

First, start with installing and activating the relevant packages tidyverse, gganimate, and gapminder if you do not have them already. Pay attention to what warning messages you get when installing gganimate, as your computer might need other packages than gifski and av

## Warning: package 'tidyverse' was built under R version 4.3.3
## Warning: package 'ggplot2' was built under R version 4.3.3
## Warning: package 'tibble' was built under R version 4.3.3
## Warning: package 'tidyr' was built under R version 4.3.3
## Warning: package 'readr' was built under R version 4.3.3
## Warning: package 'purrr' was built under R version 4.3.3
## Warning: package 'dplyr' was built under R version 4.3.3
## Warning: package 'forcats' was built under R version 4.3.3
## Warning: package 'lubridate' was built under R version 4.3.3
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.0.4     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
## Warning: package 'gganimate' was built under R version 4.3.3
## Warning: package 'gifski' was built under R version 4.3.3
## Warning: package 'av' was built under R version 4.3.3
## Warning: package 'gapminder' was built under R version 4.3.3

Look at the data and tackle the tasks

First, see which specific years are actually represented in the dataset and what variables are being recorded for each country. Note that when you run the cell below, Rmarkdown will give you two results - one for each line - that you can flip between.

str(gapminder)
## tibble [1,704 × 6] (S3: tbl_df/tbl/data.frame)
##  $ country  : Factor w/ 142 levels "Afghanistan",..: 1 1 1 1 1 1 1 1 1 1 ...
##  $ continent: Factor w/ 5 levels "Africa","Americas",..: 3 3 3 3 3 3 3 3 3 3 ...
##  $ year     : int [1:1704] 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
##  $ lifeExp  : num [1:1704] 28.8 30.3 32 34 36.1 ...
##  $ pop      : int [1:1704] 8425333 9240934 10267083 11537966 13079460 14880372 12881816 13867957 16317921 22227415 ...
##  $ gdpPercap: num [1:1704] 779 821 853 836 740 ...
unique(gapminder$year)
##  [1] 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007
head(gapminder)
## # A tibble: 6 × 6
##   country     continent  year lifeExp      pop gdpPercap
##   <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
## 1 Afghanistan Asia       1952    28.8  8425333      779.
## 2 Afghanistan Asia       1957    30.3  9240934      821.
## 3 Afghanistan Asia       1962    32.0 10267083      853.
## 4 Afghanistan Asia       1967    34.0 11537966      836.
## 5 Afghanistan Asia       1972    36.1 13079460      740.
## 6 Afghanistan Asia       1977    38.4 14880372      786.

The dataset contains information on each country in the sampled year, its continent, life expectancy, population, and GDP per capita.

Let’s plot all the countries in 1952.

theme_set(theme_bw())  # set theme to white background for better visibility

ggplot(subset(gapminder, year == 1952), aes(gdpPercap, lifeExp, size = pop)) +
  geom_point() +
  scale_x_log10() +
  ggtitle("Figure 01")

…

We see an interesting spread with an outlier to the right. Explore who it is so you can answer question 2 below!

Next, you can generate a similar plot for 2007 and compare the differences

ggplot(subset(gapminder, year == 2007), aes(gdpPercap, lifeExp, size = pop)) +
  geom_point() +
  scale_x_log10() +
  ggtitle("Figure 02")

…

The black bubbles are a bit hard to read, the comparison would be easier with a bit more visual differentiation.

Questions for the static figures:

  1. Answer: why does it make sense to have a log10 scale (scale_x_log10()) on the x axis? (hint: try to comment it out and observe the result, as in put , around the scale_x_log10() + like this: , scale_x_log10() +,. It makes the graph very flat on the x axis)

Since it takes into account the exponential growth of human development in the timeperiod we are working with. Thus making the graph more legible

  1. Answer: In Figure 1: Who is the outlier (the richest country in 1952) far right on the x axis? The following code should show a table with the richest countries in descending order with the single most prosporus/the outlier being kuwait who is a whole order of magnitude richer in terms of gdp per capita.
# Filter the data for the year 1952
gapminder_1952 <- gapminder %>% filter(year == 1952)

# Sort the data by GDP per capita in descending order
gapminder_1952_sorted <- gapminder_1952 %>% arrange(desc(gdpPercap))

# View the sorted data
head(gapminder_1952_sorted)
  1. Fix Figures 1 and 2: Differentiate the continents by color, and fix the axis labels and units to be more legible (Hint: the 2.50e+08 is so called “scientific notation”. You want to eliminate it.)
# Load the scales package for formatting
library(scales)

# Plot for 1952 with scientific notation removed
ggplot(subset(gapminder, year == 1952), aes(gdpPercap, lifeExp, size = pop)) +
  geom_point() +
  scale_x_log10() +
  scale_size_continuous(labels = label_number()) +  # Remove scientific notation for population
  ggtitle("Figure 01: 1952") +
  labs(x = "GDP per Capita (log scale)", y = "Life Expectancy", size = "Population")
# Plot for 1952 with continents colored and scientific notation removed
ggplot(subset(gapminder, year == 1952), aes(gdpPercap, lifeExp, size = pop, color = continent)) +
  geom_point(alpha = 0.7) +  # Add transparency to make overlapping points visible
  scale_x_log10() +
  scale_size_continuous(labels = label_number()) +  # Remove scientific notation for population
  ggtitle("Figure 01: 1952") +
  labs(x = "GDP per Capita (log scale)", y = "Life Expectancy", size = "Population", color = "Continent")
  1. Answer: What are the five richest countries in the world in 2007?
# Filter the data for the year 1952
gapminder_2007 <- gapminder %>% filter(year == 2007)

# Sort the data by GDP per capita in descending order
gapminder_2007_sorted <- gapminder_2007 %>% arrange(desc(gdpPercap))

# View the sorted data
head(gapminder_2007_sorted)

Make it move!

The comparison would be easier if we had the two graphs together, animated. We have a lovely tool in R to do this: the gganimate package. Beware that there may be other packages your operating system needs in order to glue interim images into an animation or video. Read the messages when installing the package.

Also, there are two ways of animating the gapminder ggplot.

Option 1: Animate using transition_states()

The first step is to create the object-to-be-animated

anim <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop)) +
  geom_point() +
  scale_x_log10()  # convert x to log scale
anim

…

This plot collates all the points across time. The next step is to split it into years and animate it. This may take some time, depending on the processing power of your computer (and other things you are asking it to do). Beware that the animation might appear in the bottom right ‘Viewer’ pane, not in this rmd preview. You need to knit the document to get the visual inside an html file.

anim + transition_states(year, 
                      transition_length = 1,
                      state_length = 1)

…

Notice how the animation moves jerkily, ‘jumping’ from one year to the next 12 times in total. This is a bit clunky, which is why it’s good we have another option.

Option 2 Animate using transition_time()

This option smooths the transition between different ‘frames’, because it interpolates and adds transitional years where there are gaps in the timeseries data.

anim2 <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop)) +
  geom_point() +
  scale_x_log10() + # convert x to log scale
  transition_time(year)
anim2

The much smoother movement in Option 2 will be much more noticeable if you add a title to the chart, that will page through the years corresponding to each frame.

Now, choose one of the animation options and get it to work. You may need to troubleshoot your installation of gganimate and other packages

Tasks for the animations:

  1. Can you add a title to one or both of the animations above that will change in sync with the animation? (Hint: search labeling for transition_states() and transition_time() functions respectively)

#to add a title to the previous animations I will use a function for each

anim <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, color = continent)) +
  geom_point(alpha = 0.7) +
  scale_x_log10() +
  scale_size_continuous(labels = scales::label_number()) +  # Remove scientific notation
  labs(
    title = 'Year: {closest_state}',  # Dynamic title showing the year
    x = "GDP per Capita (log scale)",
    y = "Life Expectancy",
    size = "Population",
    color = "Continent"
  ) +
  transition_states(year, transition_length = 1, state_length = 1)

# Render the animation
anim

anim2 <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, color = continent)) +
  geom_point(alpha = 0.7) +
  scale_x_log10() +
  scale_size_continuous(labels = scales::label_number()) +  # Remove scientific notation
  labs(
    title = 'Year: {frame_time}',  # Dynamic title showing the year
    x = "GDP per Capita (log scale)",
    y = "Life Expectancy",
    size = "Population",
    color = "Continent"
  ) +
  transition_time(year)

# Render the animation
anim2

#As can be seen in the two code chunks above, the “labs”/labels function change the labels of the graph.

  1. Can you made the axes’ labels and units more readable? Consider expanding the abbreviated labels as well as the scientific notation in the legend and x axis to whole numbers. Also, differentiate the countries from different continents by color

#I had kept the colouring from question 3 throughout, I am mostly just typing labels out

anim <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, color = continent)) +
  geom_point(alpha = 0.7) +
  scale_x_log10(labels = scales::label_number()) +  # Remove scientific notation on x-axis
  scale_size_continuous(labels = scales::label_number()) +  # Remove scientific notation for population
  labs(
    title = 'Year: {closest_state}',  # Dynamic title showing the year
    x = "GDP per Capita (log scale)",  # Descriptive x-axis label
    y = "Life Expectancy (years)",     # Descriptive y-axis label
    size = "Population",               # Legend title for population
    color = "Continent"                # Legend title for continent
  ) +
  theme_minimal() +  # Use a clean theme for better readability
  transition_states(year, transition_length = 1, state_length = 1)

# Render the animation
anim

anim2 <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, color = continent)) +
  geom_point(alpha = 0.7) +
  scale_x_log10(labels = scales::label_number()) +  # Remove scientific notation on x-axis
  scale_size_continuous(labels = scales::label_number()) +  # Remove scientific notation for population
  labs(
    title = 'Year: {frame_time}',  # Dynamic title showing the year
    x = "GDP per Capita (log scale)",  # Descriptive x-axis label
    y = "Life Expectancy (years)",     # Descriptive y-axis label
    size = "Population",               # Legend title for population
    color = "Continent"                # Legend title for continent
  ) +
  theme_minimal() +  # Use a clean theme for better readability
  transition_time(year)

# Render the animation
anim2

Final Question

  1. Is the world a better place today than it was in the year you were born? Answer this question using the gapminder data. Define better either as more prosperous, more free, more healthy, or suggest another measure that you can get from gapminder. Submit a 250 word answer with an illustration to Brightspace. Include a URL in your Brightspace submission that links to the coded solutions in Github. [Hint: if you wish to have more data than is in the filtered gapminder, you can load either the gapminder_unfiltered dataset or download more historical data at https://www.gapminder.org/data/ ]
# Load the additional life expectancy data
life_expectancy <- read.csv("C:/Users/Anton/OneDrive/Skrivebord/Rstudio 2025/data/life_expectancy.csv")

# View the first few rows of the data
head(life_expectancy)
##       country X1800 X1801 X1802 X1803 X1804 X1805 X1806 X1807 X1808 X1809 X1810
## 1 Afghanistan  28.2  28.2  28.2  28.2  28.2  28.2  28.1  28.1  28.1  28.1  28.1
## 2      Angola  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3     Albania  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4     Andorra    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5         UAE  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6   Argentina  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1811 X1812 X1813 X1814 X1815 X1816 X1817 X1818 X1819 X1820 X1821 X1822 X1823
## 1  28.1  28.1  28.1  28.1  28.1  28.1  28.0  28.0  28.0  28.0  28.0  28.0  28.0
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1824 X1825 X1826 X1827 X1828 X1829 X1830 X1831 X1832 X1833 X1834 X1835 X1836
## 1  28.0  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.8
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1837 X1838 X1839 X1840 X1841 X1842 X1843 X1844 X1845 X1846 X1847 X1848 X1849
## 1  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.7  27.7  27.7  27.7
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1850 X1851 X1852 X1853 X1854 X1855 X1856 X1857 X1858 X1859 X1860 X1861 X1862
## 1  27.7  27.9  28.0  28.2  28.3  28.5  28.6  28.8  28.9  29.1  29.2  29.4  29.5
## 2  27.0  27.1  27.2  27.4  27.5  27.6  27.8  27.9  28.0  28.2  28.3  28.4  28.6
## 3  35.4  35.4  35.4  35.4  35.3  35.3  35.3  35.3  35.3  35.3  35.3  35.2  35.2
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.8  31.0  31.1  31.2  31.3  31.5  31.6  31.7  31.9  32.0  32.1  32.2
## 6  33.2  33.2  33.2  33.2  33.2  33.3  33.3  33.3  33.3  33.3  33.3  33.3  33.3
##   X1863 X1864 X1865 X1866 X1867 X1868 X1869 X1870 X1871 X1872 X1873 X1874 X1875
## 1  29.7  29.8  30.0  30.1  30.3  30.4  30.6  30.7  30.9  31.0  31.2  31.3  31.5
## 2  28.7  28.8  28.9  29.1  29.2  29.3  29.5  29.6  29.7  29.9  30.0  30.1  30.3
## 3  35.2  35.2  35.2  35.2  35.1  35.1  35.1  35.1  35.1  35.1  35.1  35.0  35.0
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  32.4  32.5  32.6  32.8  32.9  33.0  33.1  33.3  33.4  33.5  33.6  33.8  33.9
## 6  33.3  33.3  33.3  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4
##   X1876 X1877 X1878 X1879 X1880 X1881 X1882 X1883 X1884 X1885 X1886 X1887 X1888
## 1  31.6  31.8  31.9  32.1  32.3  32.4  32.5  32.7  32.9  33.0  33.1  33.3  33.4
## 2  30.4  30.5  30.6  30.8  30.9  31.0  31.2  31.3  31.4  31.6  31.7  31.8  31.9
## 3  35.0  35.0  35.0  35.0  35.0  34.9  34.9  34.9  34.9  34.9  34.9  34.9  34.8
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  34.0  34.1  34.3  34.4  34.5  34.7  34.8  34.9  35.0  35.2  35.3  35.4  35.6
## 6  33.4  33.4  33.4  33.4  33.4  33.3  33.2  33.1  33.0  32.9  33.2  33.5  33.8
##   X1889 X1890 X1891 X1892 X1893 X1894 X1895 X1896 X1897 X1898 X1899 X1900 X1901
## 1  33.6  33.7  33.9  34.0  34.2  34.3  34.5  34.6  34.8  34.9  35.1  35.2  35.4
## 2  32.1  32.2  32.3  32.5  32.6  32.7  32.9  33.0  33.1  33.3  33.4  33.5  33.6
## 3  34.8  34.8  34.8  34.8  34.8  34.8  34.7  34.7  34.7  34.7  34.7  34.7  34.6
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  35.7  35.8  36.0  36.1  36.2  36.3  36.5  36.6  36.7  36.8  37.0  37.1  37.2
## 6  34.1  34.4  34.2  34.1  34.0  33.8  33.7  34.4  35.1  35.9  36.6  37.3  37.9
##   X1902 X1903 X1904 X1905 X1906 X1907 X1908 X1909 X1910 X1911 X1912 X1913 X1914
## 1  35.5  35.7  35.8  36.0  36.1  36.2  36.4  36.5  36.7  36.8  37.0  37.1  37.3
## 2  33.8  33.9  34.0  34.2  34.3  34.4  34.6  34.7  34.8  35.0  35.1  35.2  35.3
## 3  34.6  34.6  34.6  34.6  34.6  34.6  34.5  34.5  34.5  34.5  34.5  34.5  34.5
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  37.4  37.5  37.6  37.7  37.9  38.0  38.1  38.3  38.4  38.5  38.6  38.8  38.9
## 6  38.5  39.1  39.7  40.3  41.1  41.9  42.6  43.4  44.2  44.8  45.3  45.9  46.5
##   X1915 X1916 X1917 X1918 X1919 X1920 X1921 X1922 X1923 X1924 X1925 X1926 X1927
## 1  37.4  37.6  37.7  9.88  38.0  38.1  38.3  38.4  38.6  38.7  38.9  39.0  39.2
## 2  35.5  35.6  35.7 13.90  36.0  36.1  36.3  36.4  36.5  36.6  36.8  36.9  37.0
## 3  34.4  34.4  34.4 18.90  34.4  34.4  34.4  34.3  34.3  34.3  34.3  34.3  34.3
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  39.0  39.1  39.3 32.70  39.5  39.7  39.8  39.9  40.0  40.2  40.3  40.4  40.5
## 6  47.0  47.9  48.7 42.50  50.3  51.2  51.7  52.2  52.7  53.2  53.7  54.0  54.4
##   X1928 X1929 X1930 X1931 X1932 X1933 X1934 X1935 X1936 X1937 X1938 X1939 X1940
## 1  39.3  39.4  39.6  39.7  39.9  40.0  40.2  40.3  40.5  40.6  40.7  40.9  41.0
## 2  37.2  37.3  37.4  37.6  37.7  37.8  38.0  38.1  38.2  38.4  38.5  38.6  38.7
## 3  34.3  34.2  35.1  35.9  36.8  37.6  38.5  39.3  40.2  41.0  41.9  41.4  40.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  40.7  40.8  40.9  41.1  41.2  41.3  41.5  41.6  41.7  41.8  42.0  42.1  42.2
## 6  54.8  55.1  55.5  55.5  55.5  55.5  55.5  55.6  56.6  57.6  58.6  59.6  60.6
##   X1941 X1942 X1943 X1944 X1945 X1946 X1947 X1948 X1949 X1950 X1951 X1952 X1953
## 1  41.2  41.4  41.5  41.7  41.9  42.0  42.2  42.4  42.5  42.7  42.9  43.1  43.5
## 2  39.4  40.1  40.8  41.4  42.1  42.8  43.5  44.2  44.9  45.6  45.6  45.6  45.6
## 3  40.0  38.5  35.6  32.8  45.3  48.2  49.6  50.5  51.4  52.2  53.6  54.5  55.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA  74.6  74.7  74.8  75.0
## 5  42.3  42.4  42.5  42.6  42.7  45.8  49.0  52.1  55.3  58.4  58.5  58.6  58.7
## 6  61.2  61.8  62.5  63.1  63.7  63.6  63.5  63.5  63.4  63.3  63.5  64.2  64.1
##   X1954 X1955 X1956 X1957 X1958 X1959 X1960 X1961 X1962 X1963 X1964 X1965 X1966
## 1  43.3  43.9  44.1  44.3  44.5  44.7  45.0  45.3  45.5  45.7  45.9  46.1  46.3
## 2  45.6  45.5  45.7  45.8  45.9  46.1  46.3  44.8  45.0  45.2  45.4  45.6  45.8
## 3  56.1  56.3  58.0  59.3  61.0  61.7  62.5  63.3  63.3  63.8  64.4  64.8  65.5
## 4  75.1  75.2  75.3  75.4  75.5  75.6  75.7  75.8  75.9  76.0  76.2  76.3  76.4
## 5  58.8  58.9  58.8  59.3  59.6  59.7  60.3  60.8  61.3  61.6  62.1  62.6  63.0
## 6  64.7  64.5  65.2  65.2  65.4  65.4  65.3  65.7  65.8  65.8  65.8  66.1  66.6
##   X1967 X1968 X1969 X1970 X1971 X1972 X1973 X1974 X1975 X1976 X1977 X1978 X1979
## 1  46.5  46.7  46.9  47.1  47.3  47.3  47.3  47.4  47.5  47.7  47.9  46.4  44.7
## 2  46.0  46.2  46.4  46.6  46.8  47.0  47.2  47.4  47.5  47.5  47.7  47.8  48.0
## 3  66.1  66.5  67.1  67.8  68.3  68.8  69.3  69.8  70.2  70.7  71.1  71.7  71.3
## 4  76.5  76.7  76.8  77.0  77.1  77.2  77.4  77.5  77.7  77.8  78.0  78.1  78.2
## 5  63.4  63.8  64.2  64.0  64.9  65.1  65.4  65.7  66.0  66.3  66.6  67.0  67.3
## 6  66.5  66.0  65.9  66.1  66.9  67.3  67.7  67.9  68.0  67.0  67.7  69.0  69.8
##   X1980 X1981 X1982 X1983 X1984 X1985 X1986 X1987 X1988 X1989 X1990 X1991 X1992
## 1  43.7  44.3  44.1  42.3  39.9  42.0  43.3  45.9  48.5  52.7  53.8  53.8  54.2
## 2  48.1  48.2  48.2  48.2  48.4  48.6  48.6  48.6  48.6  49.4  49.7  50.3  50.3
## 3  71.3  71.3  71.4  71.2  71.4  71.9  72.3  72.2  72.4  72.5  72.8  72.6  73.2
## 4  78.3  78.4  78.5  78.5  78.6  78.7  78.8  78.8  78.9  79.0  79.0  79.1  79.2
## 5  67.6  68.0  68.1  67.9  68.4  68.5  68.5  68.5  68.5  68.6  68.7  68.7  68.8
## 6  70.2  70.3  70.9  70.7  70.8  71.7  72.0  72.1  72.1  72.3  72.5  72.7  72.8
##   X1993 X1994 X1995 X1996 X1997 X1998 X1999 X2000 X2001 X2002 X2003 X2004 X2005
## 1  54.4  53.9  54.3  54.7  54.5  53.3  54.7  54.7  54.8  55.5  56.5  57.1  57.6
## 2  49.0  50.3  51.2  51.7  51.6  50.6  51.9  52.8  53.4  54.5  55.1  55.5  56.4
## 3  73.8  74.6  74.6  74.5  72.9  74.8  75.1  75.4  76.0  75.9  75.6  75.8  76.2
## 4  79.3  79.5  79.8  80.0  80.2  80.4  80.6  80.8  80.9  81.1  81.2  81.3  81.4
## 5  68.8  68.7  68.8  68.9  69.0  69.2  69.2  69.1  69.2  69.4  69.3  69.1  69.2
## 6  73.0  73.4  73.4  73.5  73.6  73.7  73.8  74.2  74.3  74.3  74.4  74.9  75.3
##   X2006 X2007 X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015 X2016 X2017 X2018
## 1  58.0  58.5  59.2  59.9  60.5  61.0  61.4  61.9  61.9  61.9  62.0  62.9  62.7
## 2  57.0  58.0  58.8  59.5  60.2  60.8  61.4  62.1  63.0  63.5  63.9  64.2  64.6
## 3  76.9  77.5  77.6  78.0  78.1  78.1  78.2  78.3  78.2  78.1  78.2  78.3  78.4
## 4  81.5  81.7  81.8  81.8  81.8  81.9  81.9  82.0  82.0  82.0  82.1  82.1  82.1
## 5  69.5  70.0  70.4  70.6  70.8  71.0  71.2  71.6  73.0  73.2  73.4  73.5  73.7
## 6  75.4  75.3  75.7  75.8  75.9  76.0  76.2  76.3  76.5  76.5  76.2  76.3  76.5
##   X2019 X2020 X2021 X2022 X2023 X2024 X2025 X2026 X2027 X2028 X2029 X2030 X2031
## 1  63.3  62.3  61.8  62.6  64.0  64.8  65.1  65.4  65.6  65.9  66.1  66.3  66.6
## 2  65.1  64.9  64.2  64.5  65.9  66.1  66.3  66.5  66.7  66.9  67.0  67.2  67.4
## 3  78.5  76.2  75.7  76.1  77.3  79.5  79.7  79.9  80.1  80.3  80.5  80.6  80.8
## 4  82.2  78.3  79.6  82.7  82.9  83.0  83.2  83.3  83.5  83.6  83.8  83.9  84.0
## 5  73.9  73.2  73.0  73.4  74.6  74.8  74.9  75.1  75.3  75.5  75.7  75.8  76.0
## 6  76.6  75.2  74.7  75.4  77.3  77.4  77.6  77.8  77.9  78.1  78.3  78.4  78.6
##   X2032 X2033 X2034 X2035 X2036 X2037 X2038 X2039 X2040 X2041 X2042 X2043 X2044
## 1  66.8  67.0  67.2  67.4  67.6  67.8  68.0  68.2  68.3  68.5  68.7  68.9  69.0
## 2  67.6  67.8  68.0  68.1  68.3  68.4  68.6  68.8  68.9  69.1  69.3  69.4  69.6
## 3  81.0  81.2  81.4  81.5  81.7  81.9  82.1  82.2  82.4  82.6  82.7  82.9  83.0
## 4  84.1  84.3  84.4  84.5  84.7  84.8  84.9  85.0  85.2  85.3  85.4  85.5  85.7
## 5  76.2  76.3  76.5  76.6  76.8  77.0  77.1  77.3  77.4  77.6  77.7  77.8  78.0
## 6  78.8  78.9  79.1  79.3  79.4  79.6  79.8  79.9  80.1  80.3  80.4  80.6  80.7
##   X2045 X2046 X2047 X2048 X2049 X2050 X2051 X2052 X2053 X2054 X2055 X2056 X2057
## 1  69.2  69.4  69.5  69.7  69.8  70.0  70.2  70.3  70.5  70.6  70.8  70.9  71.1
## 2  69.7  69.9  70.0  70.2  70.3  70.5  70.6  70.7  70.9  71.0  71.2  71.3  71.4
## 3  83.2  83.3  83.5  83.6  83.8  83.9  84.0  84.2  84.3  84.5  84.6  84.7  84.9
## 4  85.8  85.9  86.0  86.1  86.3  86.4  86.5  86.6  86.7  86.8  87.0  87.1  87.2
## 5  78.1  78.3  78.4  78.5  78.7  78.8  78.9  79.0  79.2  79.3  79.4  79.5  79.7
## 6  80.9  81.0  81.2  81.4  81.5  81.7  81.8  82.0  82.1  82.2  82.4  82.5  82.7
##   X2058 X2059 X2060 X2061 X2062 X2063 X2064 X2065 X2066 X2067 X2068 X2069 X2070
## 1  71.2  71.3  71.5  71.6  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.8  72.9
## 2  71.6  71.7  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.7  72.9  73.0  73.1
## 3  85.0  85.1  85.2  85.4  85.5  85.6  85.7  85.9  86.0  86.1  86.2  86.3  86.5
## 4  87.3  87.4  87.5  87.7  87.8  87.9  88.0  88.1  88.2  88.3  88.5  88.6  88.7
## 5  79.8  79.9  80.0  80.2  80.3  80.4  80.5  80.6  80.8  80.9  81.0  81.1  81.2
## 6  82.8  82.9  83.1  83.2  83.3  83.5  83.6  83.7  83.8  84.0  84.1  84.2  84.3
##   X2071 X2072 X2073 X2074 X2075 X2076 X2077 X2078 X2079 X2080 X2081 X2082 X2083
## 1  73.0  73.2  73.3  73.5  73.6  73.8  73.9  74.1  74.2  74.3  74.5  74.6  74.8
## 2  73.3  73.4  73.5  73.6  73.8  73.9  74.0  74.1  74.3  74.4  74.5  74.6  74.8
## 3  86.6  86.7  86.8  86.9  87.1  87.2  87.3  87.4  87.5  87.7  87.8  87.9  88.0
## 4  88.8  88.9  89.0  89.1  89.2  89.3  89.5  89.6  89.7  89.8  89.9  90.0  90.1
## 5  81.4  81.5  81.6  81.7  81.8  82.0  82.1  82.2  82.3  82.4  82.5  82.6  82.8
## 6  84.5  84.6  84.7  84.8  84.9  85.1  85.2  85.3  85.4  85.5  85.6  85.8  85.9
##   X2084 X2085 X2086 X2087 X2088 X2089 X2090 X2091 X2092 X2093 X2094 X2095 X2096
## 1  74.9  75.1  75.2  75.4  75.5  75.6  75.8  75.9  76.1  76.2  76.4  76.5  76.7
## 2  74.9  75.0  75.1  75.3  75.4  75.5  75.6  75.8  75.9  76.0  76.1  76.3  76.4
## 3  88.1  88.2  88.4  88.5  88.6  88.7  88.8  88.9  89.0  89.2  89.3  89.4  89.5
## 4  90.2  90.3  90.5  90.6  90.7  90.8  90.9  91.0  91.1  91.3  91.4  91.5  91.6
## 5  82.9  83.0  83.1  83.2  83.3  83.4  83.5  83.7  83.8  83.9  84.0  84.1  84.2
## 6  86.0  86.1  86.2  86.3  86.5  86.6  86.7  86.8  86.9  87.0  87.2  87.3  87.4
##   X2097 X2098 X2099 X2100
## 1  76.8  77.0  77.1  77.3
## 2  76.5  76.7  76.8  76.9
## 3  89.6  89.7  89.8  90.0
## 4  91.7  91.8  91.9  92.0
## 5  84.3  84.5  84.6  84.7
## 6  87.5  87.6  87.7  87.8
# View the first few rows of the data
head(life_expectancy)
##       country X1800 X1801 X1802 X1803 X1804 X1805 X1806 X1807 X1808 X1809 X1810
## 1 Afghanistan  28.2  28.2  28.2  28.2  28.2  28.2  28.1  28.1  28.1  28.1  28.1
## 2      Angola  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3     Albania  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4     Andorra    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5         UAE  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6   Argentina  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1811 X1812 X1813 X1814 X1815 X1816 X1817 X1818 X1819 X1820 X1821 X1822 X1823
## 1  28.1  28.1  28.1  28.1  28.1  28.1  28.0  28.0  28.0  28.0  28.0  28.0  28.0
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1824 X1825 X1826 X1827 X1828 X1829 X1830 X1831 X1832 X1833 X1834 X1835 X1836
## 1  28.0  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.8
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1837 X1838 X1839 X1840 X1841 X1842 X1843 X1844 X1845 X1846 X1847 X1848 X1849
## 1  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.7  27.7  27.7  27.7
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1850 X1851 X1852 X1853 X1854 X1855 X1856 X1857 X1858 X1859 X1860 X1861 X1862
## 1  27.7  27.9  28.0  28.2  28.3  28.5  28.6  28.8  28.9  29.1  29.2  29.4  29.5
## 2  27.0  27.1  27.2  27.4  27.5  27.6  27.8  27.9  28.0  28.2  28.3  28.4  28.6
## 3  35.4  35.4  35.4  35.4  35.3  35.3  35.3  35.3  35.3  35.3  35.3  35.2  35.2
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.8  31.0  31.1  31.2  31.3  31.5  31.6  31.7  31.9  32.0  32.1  32.2
## 6  33.2  33.2  33.2  33.2  33.2  33.3  33.3  33.3  33.3  33.3  33.3  33.3  33.3
##   X1863 X1864 X1865 X1866 X1867 X1868 X1869 X1870 X1871 X1872 X1873 X1874 X1875
## 1  29.7  29.8  30.0  30.1  30.3  30.4  30.6  30.7  30.9  31.0  31.2  31.3  31.5
## 2  28.7  28.8  28.9  29.1  29.2  29.3  29.5  29.6  29.7  29.9  30.0  30.1  30.3
## 3  35.2  35.2  35.2  35.2  35.1  35.1  35.1  35.1  35.1  35.1  35.1  35.0  35.0
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  32.4  32.5  32.6  32.8  32.9  33.0  33.1  33.3  33.4  33.5  33.6  33.8  33.9
## 6  33.3  33.3  33.3  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4
##   X1876 X1877 X1878 X1879 X1880 X1881 X1882 X1883 X1884 X1885 X1886 X1887 X1888
## 1  31.6  31.8  31.9  32.1  32.3  32.4  32.5  32.7  32.9  33.0  33.1  33.3  33.4
## 2  30.4  30.5  30.6  30.8  30.9  31.0  31.2  31.3  31.4  31.6  31.7  31.8  31.9
## 3  35.0  35.0  35.0  35.0  35.0  34.9  34.9  34.9  34.9  34.9  34.9  34.9  34.8
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  34.0  34.1  34.3  34.4  34.5  34.7  34.8  34.9  35.0  35.2  35.3  35.4  35.6
## 6  33.4  33.4  33.4  33.4  33.4  33.3  33.2  33.1  33.0  32.9  33.2  33.5  33.8
##   X1889 X1890 X1891 X1892 X1893 X1894 X1895 X1896 X1897 X1898 X1899 X1900 X1901
## 1  33.6  33.7  33.9  34.0  34.2  34.3  34.5  34.6  34.8  34.9  35.1  35.2  35.4
## 2  32.1  32.2  32.3  32.5  32.6  32.7  32.9  33.0  33.1  33.3  33.4  33.5  33.6
## 3  34.8  34.8  34.8  34.8  34.8  34.8  34.7  34.7  34.7  34.7  34.7  34.7  34.6
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  35.7  35.8  36.0  36.1  36.2  36.3  36.5  36.6  36.7  36.8  37.0  37.1  37.2
## 6  34.1  34.4  34.2  34.1  34.0  33.8  33.7  34.4  35.1  35.9  36.6  37.3  37.9
##   X1902 X1903 X1904 X1905 X1906 X1907 X1908 X1909 X1910 X1911 X1912 X1913 X1914
## 1  35.5  35.7  35.8  36.0  36.1  36.2  36.4  36.5  36.7  36.8  37.0  37.1  37.3
## 2  33.8  33.9  34.0  34.2  34.3  34.4  34.6  34.7  34.8  35.0  35.1  35.2  35.3
## 3  34.6  34.6  34.6  34.6  34.6  34.6  34.5  34.5  34.5  34.5  34.5  34.5  34.5
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  37.4  37.5  37.6  37.7  37.9  38.0  38.1  38.3  38.4  38.5  38.6  38.8  38.9
## 6  38.5  39.1  39.7  40.3  41.1  41.9  42.6  43.4  44.2  44.8  45.3  45.9  46.5
##   X1915 X1916 X1917 X1918 X1919 X1920 X1921 X1922 X1923 X1924 X1925 X1926 X1927
## 1  37.4  37.6  37.7  9.88  38.0  38.1  38.3  38.4  38.6  38.7  38.9  39.0  39.2
## 2  35.5  35.6  35.7 13.90  36.0  36.1  36.3  36.4  36.5  36.6  36.8  36.9  37.0
## 3  34.4  34.4  34.4 18.90  34.4  34.4  34.4  34.3  34.3  34.3  34.3  34.3  34.3
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  39.0  39.1  39.3 32.70  39.5  39.7  39.8  39.9  40.0  40.2  40.3  40.4  40.5
## 6  47.0  47.9  48.7 42.50  50.3  51.2  51.7  52.2  52.7  53.2  53.7  54.0  54.4
##   X1928 X1929 X1930 X1931 X1932 X1933 X1934 X1935 X1936 X1937 X1938 X1939 X1940
## 1  39.3  39.4  39.6  39.7  39.9  40.0  40.2  40.3  40.5  40.6  40.7  40.9  41.0
## 2  37.2  37.3  37.4  37.6  37.7  37.8  38.0  38.1  38.2  38.4  38.5  38.6  38.7
## 3  34.3  34.2  35.1  35.9  36.8  37.6  38.5  39.3  40.2  41.0  41.9  41.4  40.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  40.7  40.8  40.9  41.1  41.2  41.3  41.5  41.6  41.7  41.8  42.0  42.1  42.2
## 6  54.8  55.1  55.5  55.5  55.5  55.5  55.5  55.6  56.6  57.6  58.6  59.6  60.6
##   X1941 X1942 X1943 X1944 X1945 X1946 X1947 X1948 X1949 X1950 X1951 X1952 X1953
## 1  41.2  41.4  41.5  41.7  41.9  42.0  42.2  42.4  42.5  42.7  42.9  43.1  43.5
## 2  39.4  40.1  40.8  41.4  42.1  42.8  43.5  44.2  44.9  45.6  45.6  45.6  45.6
## 3  40.0  38.5  35.6  32.8  45.3  48.2  49.6  50.5  51.4  52.2  53.6  54.5  55.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA  74.6  74.7  74.8  75.0
## 5  42.3  42.4  42.5  42.6  42.7  45.8  49.0  52.1  55.3  58.4  58.5  58.6  58.7
## 6  61.2  61.8  62.5  63.1  63.7  63.6  63.5  63.5  63.4  63.3  63.5  64.2  64.1
##   X1954 X1955 X1956 X1957 X1958 X1959 X1960 X1961 X1962 X1963 X1964 X1965 X1966
## 1  43.3  43.9  44.1  44.3  44.5  44.7  45.0  45.3  45.5  45.7  45.9  46.1  46.3
## 2  45.6  45.5  45.7  45.8  45.9  46.1  46.3  44.8  45.0  45.2  45.4  45.6  45.8
## 3  56.1  56.3  58.0  59.3  61.0  61.7  62.5  63.3  63.3  63.8  64.4  64.8  65.5
## 4  75.1  75.2  75.3  75.4  75.5  75.6  75.7  75.8  75.9  76.0  76.2  76.3  76.4
## 5  58.8  58.9  58.8  59.3  59.6  59.7  60.3  60.8  61.3  61.6  62.1  62.6  63.0
## 6  64.7  64.5  65.2  65.2  65.4  65.4  65.3  65.7  65.8  65.8  65.8  66.1  66.6
##   X1967 X1968 X1969 X1970 X1971 X1972 X1973 X1974 X1975 X1976 X1977 X1978 X1979
## 1  46.5  46.7  46.9  47.1  47.3  47.3  47.3  47.4  47.5  47.7  47.9  46.4  44.7
## 2  46.0  46.2  46.4  46.6  46.8  47.0  47.2  47.4  47.5  47.5  47.7  47.8  48.0
## 3  66.1  66.5  67.1  67.8  68.3  68.8  69.3  69.8  70.2  70.7  71.1  71.7  71.3
## 4  76.5  76.7  76.8  77.0  77.1  77.2  77.4  77.5  77.7  77.8  78.0  78.1  78.2
## 5  63.4  63.8  64.2  64.0  64.9  65.1  65.4  65.7  66.0  66.3  66.6  67.0  67.3
## 6  66.5  66.0  65.9  66.1  66.9  67.3  67.7  67.9  68.0  67.0  67.7  69.0  69.8
##   X1980 X1981 X1982 X1983 X1984 X1985 X1986 X1987 X1988 X1989 X1990 X1991 X1992
## 1  43.7  44.3  44.1  42.3  39.9  42.0  43.3  45.9  48.5  52.7  53.8  53.8  54.2
## 2  48.1  48.2  48.2  48.2  48.4  48.6  48.6  48.6  48.6  49.4  49.7  50.3  50.3
## 3  71.3  71.3  71.4  71.2  71.4  71.9  72.3  72.2  72.4  72.5  72.8  72.6  73.2
## 4  78.3  78.4  78.5  78.5  78.6  78.7  78.8  78.8  78.9  79.0  79.0  79.1  79.2
## 5  67.6  68.0  68.1  67.9  68.4  68.5  68.5  68.5  68.5  68.6  68.7  68.7  68.8
## 6  70.2  70.3  70.9  70.7  70.8  71.7  72.0  72.1  72.1  72.3  72.5  72.7  72.8
##   X1993 X1994 X1995 X1996 X1997 X1998 X1999 X2000 X2001 X2002 X2003 X2004 X2005
## 1  54.4  53.9  54.3  54.7  54.5  53.3  54.7  54.7  54.8  55.5  56.5  57.1  57.6
## 2  49.0  50.3  51.2  51.7  51.6  50.6  51.9  52.8  53.4  54.5  55.1  55.5  56.4
## 3  73.8  74.6  74.6  74.5  72.9  74.8  75.1  75.4  76.0  75.9  75.6  75.8  76.2
## 4  79.3  79.5  79.8  80.0  80.2  80.4  80.6  80.8  80.9  81.1  81.2  81.3  81.4
## 5  68.8  68.7  68.8  68.9  69.0  69.2  69.2  69.1  69.2  69.4  69.3  69.1  69.2
## 6  73.0  73.4  73.4  73.5  73.6  73.7  73.8  74.2  74.3  74.3  74.4  74.9  75.3
##   X2006 X2007 X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015 X2016 X2017 X2018
## 1  58.0  58.5  59.2  59.9  60.5  61.0  61.4  61.9  61.9  61.9  62.0  62.9  62.7
## 2  57.0  58.0  58.8  59.5  60.2  60.8  61.4  62.1  63.0  63.5  63.9  64.2  64.6
## 3  76.9  77.5  77.6  78.0  78.1  78.1  78.2  78.3  78.2  78.1  78.2  78.3  78.4
## 4  81.5  81.7  81.8  81.8  81.8  81.9  81.9  82.0  82.0  82.0  82.1  82.1  82.1
## 5  69.5  70.0  70.4  70.6  70.8  71.0  71.2  71.6  73.0  73.2  73.4  73.5  73.7
## 6  75.4  75.3  75.7  75.8  75.9  76.0  76.2  76.3  76.5  76.5  76.2  76.3  76.5
##   X2019 X2020 X2021 X2022 X2023 X2024 X2025 X2026 X2027 X2028 X2029 X2030 X2031
## 1  63.3  62.3  61.8  62.6  64.0  64.8  65.1  65.4  65.6  65.9  66.1  66.3  66.6
## 2  65.1  64.9  64.2  64.5  65.9  66.1  66.3  66.5  66.7  66.9  67.0  67.2  67.4
## 3  78.5  76.2  75.7  76.1  77.3  79.5  79.7  79.9  80.1  80.3  80.5  80.6  80.8
## 4  82.2  78.3  79.6  82.7  82.9  83.0  83.2  83.3  83.5  83.6  83.8  83.9  84.0
## 5  73.9  73.2  73.0  73.4  74.6  74.8  74.9  75.1  75.3  75.5  75.7  75.8  76.0
## 6  76.6  75.2  74.7  75.4  77.3  77.4  77.6  77.8  77.9  78.1  78.3  78.4  78.6
##   X2032 X2033 X2034 X2035 X2036 X2037 X2038 X2039 X2040 X2041 X2042 X2043 X2044
## 1  66.8  67.0  67.2  67.4  67.6  67.8  68.0  68.2  68.3  68.5  68.7  68.9  69.0
## 2  67.6  67.8  68.0  68.1  68.3  68.4  68.6  68.8  68.9  69.1  69.3  69.4  69.6
## 3  81.0  81.2  81.4  81.5  81.7  81.9  82.1  82.2  82.4  82.6  82.7  82.9  83.0
## 4  84.1  84.3  84.4  84.5  84.7  84.8  84.9  85.0  85.2  85.3  85.4  85.5  85.7
## 5  76.2  76.3  76.5  76.6  76.8  77.0  77.1  77.3  77.4  77.6  77.7  77.8  78.0
## 6  78.8  78.9  79.1  79.3  79.4  79.6  79.8  79.9  80.1  80.3  80.4  80.6  80.7
##   X2045 X2046 X2047 X2048 X2049 X2050 X2051 X2052 X2053 X2054 X2055 X2056 X2057
## 1  69.2  69.4  69.5  69.7  69.8  70.0  70.2  70.3  70.5  70.6  70.8  70.9  71.1
## 2  69.7  69.9  70.0  70.2  70.3  70.5  70.6  70.7  70.9  71.0  71.2  71.3  71.4
## 3  83.2  83.3  83.5  83.6  83.8  83.9  84.0  84.2  84.3  84.5  84.6  84.7  84.9
## 4  85.8  85.9  86.0  86.1  86.3  86.4  86.5  86.6  86.7  86.8  87.0  87.1  87.2
## 5  78.1  78.3  78.4  78.5  78.7  78.8  78.9  79.0  79.2  79.3  79.4  79.5  79.7
## 6  80.9  81.0  81.2  81.4  81.5  81.7  81.8  82.0  82.1  82.2  82.4  82.5  82.7
##   X2058 X2059 X2060 X2061 X2062 X2063 X2064 X2065 X2066 X2067 X2068 X2069 X2070
## 1  71.2  71.3  71.5  71.6  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.8  72.9
## 2  71.6  71.7  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.7  72.9  73.0  73.1
## 3  85.0  85.1  85.2  85.4  85.5  85.6  85.7  85.9  86.0  86.1  86.2  86.3  86.5
## 4  87.3  87.4  87.5  87.7  87.8  87.9  88.0  88.1  88.2  88.3  88.5  88.6  88.7
## 5  79.8  79.9  80.0  80.2  80.3  80.4  80.5  80.6  80.8  80.9  81.0  81.1  81.2
## 6  82.8  82.9  83.1  83.2  83.3  83.5  83.6  83.7  83.8  84.0  84.1  84.2  84.3
##   X2071 X2072 X2073 X2074 X2075 X2076 X2077 X2078 X2079 X2080 X2081 X2082 X2083
## 1  73.0  73.2  73.3  73.5  73.6  73.8  73.9  74.1  74.2  74.3  74.5  74.6  74.8
## 2  73.3  73.4  73.5  73.6  73.8  73.9  74.0  74.1  74.3  74.4  74.5  74.6  74.8
## 3  86.6  86.7  86.8  86.9  87.1  87.2  87.3  87.4  87.5  87.7  87.8  87.9  88.0
## 4  88.8  88.9  89.0  89.1  89.2  89.3  89.5  89.6  89.7  89.8  89.9  90.0  90.1
## 5  81.4  81.5  81.6  81.7  81.8  82.0  82.1  82.2  82.3  82.4  82.5  82.6  82.8
## 6  84.5  84.6  84.7  84.8  84.9  85.1  85.2  85.3  85.4  85.5  85.6  85.8  85.9
##   X2084 X2085 X2086 X2087 X2088 X2089 X2090 X2091 X2092 X2093 X2094 X2095 X2096
## 1  74.9  75.1  75.2  75.4  75.5  75.6  75.8  75.9  76.1  76.2  76.4  76.5  76.7
## 2  74.9  75.0  75.1  75.3  75.4  75.5  75.6  75.8  75.9  76.0  76.1  76.3  76.4
## 3  88.1  88.2  88.4  88.5  88.6  88.7  88.8  88.9  89.0  89.2  89.3  89.4  89.5
## 4  90.2  90.3  90.5  90.6  90.7  90.8  90.9  91.0  91.1  91.3  91.4  91.5  91.6
## 5  82.9  83.0  83.1  83.2  83.3  83.4  83.5  83.7  83.8  83.9  84.0  84.1  84.2
## 6  86.0  86.1  86.2  86.3  86.5  86.6  86.7  86.8  86.9  87.0  87.2  87.3  87.4
##   X2097 X2098 X2099 X2100
## 1  76.8  77.0  77.1  77.3
## 2  76.5  76.7  76.8  76.9
## 3  89.6  89.7  89.8  90.0
## 4  91.7  91.8  91.9  92.0
## 5  84.3  84.5  84.6  84.7
## 6  87.5  87.6  87.7  87.8
# Check the column names
colnames(life_expectancy)
##   [1] "country" "X1800"   "X1801"   "X1802"   "X1803"   "X1804"   "X1805"  
##   [8] "X1806"   "X1807"   "X1808"   "X1809"   "X1810"   "X1811"   "X1812"  
##  [15] "X1813"   "X1814"   "X1815"   "X1816"   "X1817"   "X1818"   "X1819"  
##  [22] "X1820"   "X1821"   "X1822"   "X1823"   "X1824"   "X1825"   "X1826"  
##  [29] "X1827"   "X1828"   "X1829"   "X1830"   "X1831"   "X1832"   "X1833"  
##  [36] "X1834"   "X1835"   "X1836"   "X1837"   "X1838"   "X1839"   "X1840"  
##  [43] "X1841"   "X1842"   "X1843"   "X1844"   "X1845"   "X1846"   "X1847"  
##  [50] "X1848"   "X1849"   "X1850"   "X1851"   "X1852"   "X1853"   "X1854"  
##  [57] "X1855"   "X1856"   "X1857"   "X1858"   "X1859"   "X1860"   "X1861"  
##  [64] "X1862"   "X1863"   "X1864"   "X1865"   "X1866"   "X1867"   "X1868"  
##  [71] "X1869"   "X1870"   "X1871"   "X1872"   "X1873"   "X1874"   "X1875"  
##  [78] "X1876"   "X1877"   "X1878"   "X1879"   "X1880"   "X1881"   "X1882"  
##  [85] "X1883"   "X1884"   "X1885"   "X1886"   "X1887"   "X1888"   "X1889"  
##  [92] "X1890"   "X1891"   "X1892"   "X1893"   "X1894"   "X1895"   "X1896"  
##  [99] "X1897"   "X1898"   "X1899"   "X1900"   "X1901"   "X1902"   "X1903"  
## [106] "X1904"   "X1905"   "X1906"   "X1907"   "X1908"   "X1909"   "X1910"  
## [113] "X1911"   "X1912"   "X1913"   "X1914"   "X1915"   "X1916"   "X1917"  
## [120] "X1918"   "X1919"   "X1920"   "X1921"   "X1922"   "X1923"   "X1924"  
## [127] "X1925"   "X1926"   "X1927"   "X1928"   "X1929"   "X1930"   "X1931"  
## [134] "X1932"   "X1933"   "X1934"   "X1935"   "X1936"   "X1937"   "X1938"  
## [141] "X1939"   "X1940"   "X1941"   "X1942"   "X1943"   "X1944"   "X1945"  
## [148] "X1946"   "X1947"   "X1948"   "X1949"   "X1950"   "X1951"   "X1952"  
## [155] "X1953"   "X1954"   "X1955"   "X1956"   "X1957"   "X1958"   "X1959"  
## [162] "X1960"   "X1961"   "X1962"   "X1963"   "X1964"   "X1965"   "X1966"  
## [169] "X1967"   "X1968"   "X1969"   "X1970"   "X1971"   "X1972"   "X1973"  
## [176] "X1974"   "X1975"   "X1976"   "X1977"   "X1978"   "X1979"   "X1980"  
## [183] "X1981"   "X1982"   "X1983"   "X1984"   "X1985"   "X1986"   "X1987"  
## [190] "X1988"   "X1989"   "X1990"   "X1991"   "X1992"   "X1993"   "X1994"  
## [197] "X1995"   "X1996"   "X1997"   "X1998"   "X1999"   "X2000"   "X2001"  
## [204] "X2002"   "X2003"   "X2004"   "X2005"   "X2006"   "X2007"   "X2008"  
## [211] "X2009"   "X2010"   "X2011"   "X2012"   "X2013"   "X2014"   "X2015"  
## [218] "X2016"   "X2017"   "X2018"   "X2019"   "X2020"   "X2021"   "X2022"  
## [225] "X2023"   "X2024"   "X2025"   "X2026"   "X2027"   "X2028"   "X2029"  
## [232] "X2030"   "X2031"   "X2032"   "X2033"   "X2034"   "X2035"   "X2036"  
## [239] "X2037"   "X2038"   "X2039"   "X2040"   "X2041"   "X2042"   "X2043"  
## [246] "X2044"   "X2045"   "X2046"   "X2047"   "X2048"   "X2049"   "X2050"  
## [253] "X2051"   "X2052"   "X2053"   "X2054"   "X2055"   "X2056"   "X2057"  
## [260] "X2058"   "X2059"   "X2060"   "X2061"   "X2062"   "X2063"   "X2064"  
## [267] "X2065"   "X2066"   "X2067"   "X2068"   "X2069"   "X2070"   "X2071"  
## [274] "X2072"   "X2073"   "X2074"   "X2075"   "X2076"   "X2077"   "X2078"  
## [281] "X2079"   "X2080"   "X2081"   "X2082"   "X2083"   "X2084"   "X2085"  
## [288] "X2086"   "X2087"   "X2088"   "X2089"   "X2090"   "X2091"   "X2092"  
## [295] "X2093"   "X2094"   "X2095"   "X2096"   "X2097"   "X2098"   "X2099"  
## [302] "X2100"
# Check the structure of the data
str(life_expectancy)
## 'data.frame':    196 obs. of  302 variables:
##  $ country: chr  "Afghanistan" "Angola" "Albania" "Andorra" ...
##  $ X1800  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1801  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1802  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1803  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1804  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1805  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1806  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1807  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1808  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1809  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1810  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1811  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1812  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1813  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1814  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1815  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1816  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1817  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1818  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1819  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1820  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1821  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1822  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1823  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1824  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1825  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1826  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1827  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1828  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1829  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1830  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1831  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1832  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1833  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1834  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1835  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1836  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1837  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1838  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1839  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1840  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1841  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1842  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1843  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1844  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1845  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1846  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1847  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1848  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1849  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1850  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1851  : num  27.9 27.1 35.4 NA 30.8 33.2 33.9 33.5 34 34.4 ...
##  $ X1852  : num  28 27.2 35.4 NA 31 33.2 33.9 33.5 34 34.4 ...
##  $ X1853  : num  28.2 27.4 35.4 NA 31.1 33.2 33.8 33.5 34.1 34.4 ...
##  $ X1854  : num  28.3 27.5 35.3 NA 31.2 33.2 33.7 33.5 34.1 34.4 ...
##  $ X1855  : num  28.5 27.6 35.3 NA 31.3 33.3 33.6 33.5 34.1 34.4 ...
##  $ X1856  : num  28.6 27.8 35.3 NA 31.5 33.3 33.5 33.5 34.1 34.4 ...
##  $ X1857  : num  28.8 27.9 35.3 NA 31.6 33.3 33.5 33.5 34.1 34.4 ...
##  $ X1858  : num  28.9 28 35.3 NA 31.7 33.3 33.4 33.5 34.1 34.4 ...
##  $ X1859  : num  29.1 28.2 35.3 NA 31.9 33.3 33.3 33.5 34.1 34.4 ...
##  $ X1860  : num  29.2 28.3 35.3 NA 32 33.3 33.2 33.5 34.1 34.4 ...
##  $ X1861  : num  29.4 28.4 35.2 NA 32.1 33.3 33.1 33.5 34.1 34.4 ...
##  $ X1862  : num  29.5 28.6 35.2 NA 32.2 33.3 33.1 33.5 34.1 34.4 ...
##  $ X1863  : num  29.7 28.7 35.2 NA 32.4 33.3 33 33.5 34.1 34.4 ...
##  $ X1864  : num  29.8 28.8 35.2 NA 32.5 33.3 32.4 33.5 34.1 34.4 ...
##  $ X1865  : num  30 28.9 35.2 NA 32.6 33.3 31.8 33.5 34.1 34.4 ...
##  $ X1866  : num  30.1 29.1 35.2 NA 32.8 33.4 31.2 33.6 34.1 34.4 ...
##  $ X1867  : num  30.3 29.2 35.1 NA 32.9 33.4 30.7 33.6 34.1 34.4 ...
##  $ X1868  : num  30.4 29.3 35.1 NA 33 33.4 30.1 33.6 34.1 34.4 ...
##  $ X1869  : num  30.6 29.5 35.1 NA 33.1 33.4 30.1 33.6 34.1 34.4 ...
##  $ X1870  : num  30.7 29.6 35.1 NA 33.3 33.4 30 33.6 34.1 34.4 ...
##  $ X1871  : num  30.9 29.7 35.1 NA 33.4 33.4 30 33.6 34.6 34.4 ...
##  $ X1872  : num  31 29.9 35.1 NA 33.5 33.4 30 33.6 35.1 34.5 ...
##  $ X1873  : num  31.2 30 35.1 NA 33.6 33.4 29.9 33.6 35.7 34.5 ...
##  $ X1874  : num  31.3 30.1 35 NA 33.8 33.4 30.1 33.6 36.2 34.6 ...
##  $ X1875  : num  31.5 30.3 35 NA 33.9 33.4 30.2 33.6 36.8 34.7 ...
##  $ X1876  : num  31.6 30.4 35 NA 34 33.4 30.3 33.6 37.3 34.7 ...
##  $ X1877  : num  31.8 30.5 35 NA 34.1 33.4 30.4 33.6 37.8 34.8 ...
##  $ X1878  : num  31.9 30.6 35 NA 34.3 33.4 30.5 33.6 38.3 34.8 ...
##  $ X1879  : num  32.1 30.8 35 NA 34.4 33.4 30.6 33.6 38.9 34.9 ...
##  $ X1880  : num  32.3 30.9 35 NA 34.5 33.4 30.8 33.6 39.4 34.9 ...
##  $ X1881  : num  32.4 31 34.9 NA 34.7 33.3 30.9 33.6 39.9 35 ...
##  $ X1882  : num  32.5 31.2 34.9 NA 34.8 33.2 31 33.6 40.5 35.2 ...
##  $ X1883  : num  32.7 31.3 34.9 NA 34.9 33.1 31.1 33.6 41 35.5 ...
##  $ X1884  : num  32.9 31.4 34.9 NA 35 33 31.2 33.6 41.5 35.7 ...
##  $ X1885  : num  33 31.6 34.9 NA 35.2 32.9 31.3 33.6 42.1 35.9 ...
##  $ X1886  : num  33.1 31.7 34.9 NA 35.3 33.2 31.4 33.6 42.6 36.1 ...
##  $ X1887  : num  33.3 31.8 34.9 NA 35.4 33.5 31.5 33.6 43.1 36.4 ...
##  $ X1888  : num  33.4 31.9 34.8 NA 35.6 33.8 31.6 33.6 43.7 36.6 ...
##  $ X1889  : num  33.6 32.1 34.8 NA 35.7 34.1 31.7 33.6 44.2 36.8 ...
##  $ X1890  : num  33.7 32.2 34.8 NA 35.8 34.4 31.8 33.6 44.7 37 ...
##  $ X1891  : num  33.9 32.3 34.8 NA 36 34.2 31.9 33.6 45.3 37.3 ...
##  $ X1892  : num  34 32.5 34.8 NA 36.1 34.1 32 33.6 45.8 37.8 ...
##  $ X1893  : num  34.2 32.6 34.8 NA 36.2 34 32.1 33.6 46.3 38.2 ...
##  $ X1894  : num  34.3 32.7 34.8 NA 36.3 33.8 32.2 33.6 46.9 38.7 ...
##  $ X1895  : num  34.5 32.9 34.7 NA 36.5 33.7 32.3 33.6 47.4 39.2 ...
##  $ X1896  : num  34.6 33 34.7 NA 36.6 34.4 32.4 33.6 47.9 39.6 ...
##  $ X1897  : num  34.8 33.1 34.7 NA 36.7 35.1 32.5 33.6 48.5 40.1 ...
##   [list output truncated]
# View the first few rows of the data
head(life_expectancy)
##       country X1800 X1801 X1802 X1803 X1804 X1805 X1806 X1807 X1808 X1809 X1810
## 1 Afghanistan  28.2  28.2  28.2  28.2  28.2  28.2  28.1  28.1  28.1  28.1  28.1
## 2      Angola  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3     Albania  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4     Andorra    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5         UAE  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6   Argentina  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1811 X1812 X1813 X1814 X1815 X1816 X1817 X1818 X1819 X1820 X1821 X1822 X1823
## 1  28.1  28.1  28.1  28.1  28.1  28.1  28.0  28.0  28.0  28.0  28.0  28.0  28.0
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1824 X1825 X1826 X1827 X1828 X1829 X1830 X1831 X1832 X1833 X1834 X1835 X1836
## 1  28.0  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.8
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1837 X1838 X1839 X1840 X1841 X1842 X1843 X1844 X1845 X1846 X1847 X1848 X1849
## 1  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.7  27.7  27.7  27.7
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1850 X1851 X1852 X1853 X1854 X1855 X1856 X1857 X1858 X1859 X1860 X1861 X1862
## 1  27.7  27.9  28.0  28.2  28.3  28.5  28.6  28.8  28.9  29.1  29.2  29.4  29.5
## 2  27.0  27.1  27.2  27.4  27.5  27.6  27.8  27.9  28.0  28.2  28.3  28.4  28.6
## 3  35.4  35.4  35.4  35.4  35.3  35.3  35.3  35.3  35.3  35.3  35.3  35.2  35.2
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.8  31.0  31.1  31.2  31.3  31.5  31.6  31.7  31.9  32.0  32.1  32.2
## 6  33.2  33.2  33.2  33.2  33.2  33.3  33.3  33.3  33.3  33.3  33.3  33.3  33.3
##   X1863 X1864 X1865 X1866 X1867 X1868 X1869 X1870 X1871 X1872 X1873 X1874 X1875
## 1  29.7  29.8  30.0  30.1  30.3  30.4  30.6  30.7  30.9  31.0  31.2  31.3  31.5
## 2  28.7  28.8  28.9  29.1  29.2  29.3  29.5  29.6  29.7  29.9  30.0  30.1  30.3
## 3  35.2  35.2  35.2  35.2  35.1  35.1  35.1  35.1  35.1  35.1  35.1  35.0  35.0
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  32.4  32.5  32.6  32.8  32.9  33.0  33.1  33.3  33.4  33.5  33.6  33.8  33.9
## 6  33.3  33.3  33.3  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4
##   X1876 X1877 X1878 X1879 X1880 X1881 X1882 X1883 X1884 X1885 X1886 X1887 X1888
## 1  31.6  31.8  31.9  32.1  32.3  32.4  32.5  32.7  32.9  33.0  33.1  33.3  33.4
## 2  30.4  30.5  30.6  30.8  30.9  31.0  31.2  31.3  31.4  31.6  31.7  31.8  31.9
## 3  35.0  35.0  35.0  35.0  35.0  34.9  34.9  34.9  34.9  34.9  34.9  34.9  34.8
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  34.0  34.1  34.3  34.4  34.5  34.7  34.8  34.9  35.0  35.2  35.3  35.4  35.6
## 6  33.4  33.4  33.4  33.4  33.4  33.3  33.2  33.1  33.0  32.9  33.2  33.5  33.8
##   X1889 X1890 X1891 X1892 X1893 X1894 X1895 X1896 X1897 X1898 X1899 X1900 X1901
## 1  33.6  33.7  33.9  34.0  34.2  34.3  34.5  34.6  34.8  34.9  35.1  35.2  35.4
## 2  32.1  32.2  32.3  32.5  32.6  32.7  32.9  33.0  33.1  33.3  33.4  33.5  33.6
## 3  34.8  34.8  34.8  34.8  34.8  34.8  34.7  34.7  34.7  34.7  34.7  34.7  34.6
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  35.7  35.8  36.0  36.1  36.2  36.3  36.5  36.6  36.7  36.8  37.0  37.1  37.2
## 6  34.1  34.4  34.2  34.1  34.0  33.8  33.7  34.4  35.1  35.9  36.6  37.3  37.9
##   X1902 X1903 X1904 X1905 X1906 X1907 X1908 X1909 X1910 X1911 X1912 X1913 X1914
## 1  35.5  35.7  35.8  36.0  36.1  36.2  36.4  36.5  36.7  36.8  37.0  37.1  37.3
## 2  33.8  33.9  34.0  34.2  34.3  34.4  34.6  34.7  34.8  35.0  35.1  35.2  35.3
## 3  34.6  34.6  34.6  34.6  34.6  34.6  34.5  34.5  34.5  34.5  34.5  34.5  34.5
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  37.4  37.5  37.6  37.7  37.9  38.0  38.1  38.3  38.4  38.5  38.6  38.8  38.9
## 6  38.5  39.1  39.7  40.3  41.1  41.9  42.6  43.4  44.2  44.8  45.3  45.9  46.5
##   X1915 X1916 X1917 X1918 X1919 X1920 X1921 X1922 X1923 X1924 X1925 X1926 X1927
## 1  37.4  37.6  37.7  9.88  38.0  38.1  38.3  38.4  38.6  38.7  38.9  39.0  39.2
## 2  35.5  35.6  35.7 13.90  36.0  36.1  36.3  36.4  36.5  36.6  36.8  36.9  37.0
## 3  34.4  34.4  34.4 18.90  34.4  34.4  34.4  34.3  34.3  34.3  34.3  34.3  34.3
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  39.0  39.1  39.3 32.70  39.5  39.7  39.8  39.9  40.0  40.2  40.3  40.4  40.5
## 6  47.0  47.9  48.7 42.50  50.3  51.2  51.7  52.2  52.7  53.2  53.7  54.0  54.4
##   X1928 X1929 X1930 X1931 X1932 X1933 X1934 X1935 X1936 X1937 X1938 X1939 X1940
## 1  39.3  39.4  39.6  39.7  39.9  40.0  40.2  40.3  40.5  40.6  40.7  40.9  41.0
## 2  37.2  37.3  37.4  37.6  37.7  37.8  38.0  38.1  38.2  38.4  38.5  38.6  38.7
## 3  34.3  34.2  35.1  35.9  36.8  37.6  38.5  39.3  40.2  41.0  41.9  41.4  40.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  40.7  40.8  40.9  41.1  41.2  41.3  41.5  41.6  41.7  41.8  42.0  42.1  42.2
## 6  54.8  55.1  55.5  55.5  55.5  55.5  55.5  55.6  56.6  57.6  58.6  59.6  60.6
##   X1941 X1942 X1943 X1944 X1945 X1946 X1947 X1948 X1949 X1950 X1951 X1952 X1953
## 1  41.2  41.4  41.5  41.7  41.9  42.0  42.2  42.4  42.5  42.7  42.9  43.1  43.5
## 2  39.4  40.1  40.8  41.4  42.1  42.8  43.5  44.2  44.9  45.6  45.6  45.6  45.6
## 3  40.0  38.5  35.6  32.8  45.3  48.2  49.6  50.5  51.4  52.2  53.6  54.5  55.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA  74.6  74.7  74.8  75.0
## 5  42.3  42.4  42.5  42.6  42.7  45.8  49.0  52.1  55.3  58.4  58.5  58.6  58.7
## 6  61.2  61.8  62.5  63.1  63.7  63.6  63.5  63.5  63.4  63.3  63.5  64.2  64.1
##   X1954 X1955 X1956 X1957 X1958 X1959 X1960 X1961 X1962 X1963 X1964 X1965 X1966
## 1  43.3  43.9  44.1  44.3  44.5  44.7  45.0  45.3  45.5  45.7  45.9  46.1  46.3
## 2  45.6  45.5  45.7  45.8  45.9  46.1  46.3  44.8  45.0  45.2  45.4  45.6  45.8
## 3  56.1  56.3  58.0  59.3  61.0  61.7  62.5  63.3  63.3  63.8  64.4  64.8  65.5
## 4  75.1  75.2  75.3  75.4  75.5  75.6  75.7  75.8  75.9  76.0  76.2  76.3  76.4
## 5  58.8  58.9  58.8  59.3  59.6  59.7  60.3  60.8  61.3  61.6  62.1  62.6  63.0
## 6  64.7  64.5  65.2  65.2  65.4  65.4  65.3  65.7  65.8  65.8  65.8  66.1  66.6
##   X1967 X1968 X1969 X1970 X1971 X1972 X1973 X1974 X1975 X1976 X1977 X1978 X1979
## 1  46.5  46.7  46.9  47.1  47.3  47.3  47.3  47.4  47.5  47.7  47.9  46.4  44.7
## 2  46.0  46.2  46.4  46.6  46.8  47.0  47.2  47.4  47.5  47.5  47.7  47.8  48.0
## 3  66.1  66.5  67.1  67.8  68.3  68.8  69.3  69.8  70.2  70.7  71.1  71.7  71.3
## 4  76.5  76.7  76.8  77.0  77.1  77.2  77.4  77.5  77.7  77.8  78.0  78.1  78.2
## 5  63.4  63.8  64.2  64.0  64.9  65.1  65.4  65.7  66.0  66.3  66.6  67.0  67.3
## 6  66.5  66.0  65.9  66.1  66.9  67.3  67.7  67.9  68.0  67.0  67.7  69.0  69.8
##   X1980 X1981 X1982 X1983 X1984 X1985 X1986 X1987 X1988 X1989 X1990 X1991 X1992
## 1  43.7  44.3  44.1  42.3  39.9  42.0  43.3  45.9  48.5  52.7  53.8  53.8  54.2
## 2  48.1  48.2  48.2  48.2  48.4  48.6  48.6  48.6  48.6  49.4  49.7  50.3  50.3
## 3  71.3  71.3  71.4  71.2  71.4  71.9  72.3  72.2  72.4  72.5  72.8  72.6  73.2
## 4  78.3  78.4  78.5  78.5  78.6  78.7  78.8  78.8  78.9  79.0  79.0  79.1  79.2
## 5  67.6  68.0  68.1  67.9  68.4  68.5  68.5  68.5  68.5  68.6  68.7  68.7  68.8
## 6  70.2  70.3  70.9  70.7  70.8  71.7  72.0  72.1  72.1  72.3  72.5  72.7  72.8
##   X1993 X1994 X1995 X1996 X1997 X1998 X1999 X2000 X2001 X2002 X2003 X2004 X2005
## 1  54.4  53.9  54.3  54.7  54.5  53.3  54.7  54.7  54.8  55.5  56.5  57.1  57.6
## 2  49.0  50.3  51.2  51.7  51.6  50.6  51.9  52.8  53.4  54.5  55.1  55.5  56.4
## 3  73.8  74.6  74.6  74.5  72.9  74.8  75.1  75.4  76.0  75.9  75.6  75.8  76.2
## 4  79.3  79.5  79.8  80.0  80.2  80.4  80.6  80.8  80.9  81.1  81.2  81.3  81.4
## 5  68.8  68.7  68.8  68.9  69.0  69.2  69.2  69.1  69.2  69.4  69.3  69.1  69.2
## 6  73.0  73.4  73.4  73.5  73.6  73.7  73.8  74.2  74.3  74.3  74.4  74.9  75.3
##   X2006 X2007 X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015 X2016 X2017 X2018
## 1  58.0  58.5  59.2  59.9  60.5  61.0  61.4  61.9  61.9  61.9  62.0  62.9  62.7
## 2  57.0  58.0  58.8  59.5  60.2  60.8  61.4  62.1  63.0  63.5  63.9  64.2  64.6
## 3  76.9  77.5  77.6  78.0  78.1  78.1  78.2  78.3  78.2  78.1  78.2  78.3  78.4
## 4  81.5  81.7  81.8  81.8  81.8  81.9  81.9  82.0  82.0  82.0  82.1  82.1  82.1
## 5  69.5  70.0  70.4  70.6  70.8  71.0  71.2  71.6  73.0  73.2  73.4  73.5  73.7
## 6  75.4  75.3  75.7  75.8  75.9  76.0  76.2  76.3  76.5  76.5  76.2  76.3  76.5
##   X2019 X2020 X2021 X2022 X2023 X2024 X2025 X2026 X2027 X2028 X2029 X2030 X2031
## 1  63.3  62.3  61.8  62.6  64.0  64.8  65.1  65.4  65.6  65.9  66.1  66.3  66.6
## 2  65.1  64.9  64.2  64.5  65.9  66.1  66.3  66.5  66.7  66.9  67.0  67.2  67.4
## 3  78.5  76.2  75.7  76.1  77.3  79.5  79.7  79.9  80.1  80.3  80.5  80.6  80.8
## 4  82.2  78.3  79.6  82.7  82.9  83.0  83.2  83.3  83.5  83.6  83.8  83.9  84.0
## 5  73.9  73.2  73.0  73.4  74.6  74.8  74.9  75.1  75.3  75.5  75.7  75.8  76.0
## 6  76.6  75.2  74.7  75.4  77.3  77.4  77.6  77.8  77.9  78.1  78.3  78.4  78.6
##   X2032 X2033 X2034 X2035 X2036 X2037 X2038 X2039 X2040 X2041 X2042 X2043 X2044
## 1  66.8  67.0  67.2  67.4  67.6  67.8  68.0  68.2  68.3  68.5  68.7  68.9  69.0
## 2  67.6  67.8  68.0  68.1  68.3  68.4  68.6  68.8  68.9  69.1  69.3  69.4  69.6
## 3  81.0  81.2  81.4  81.5  81.7  81.9  82.1  82.2  82.4  82.6  82.7  82.9  83.0
## 4  84.1  84.3  84.4  84.5  84.7  84.8  84.9  85.0  85.2  85.3  85.4  85.5  85.7
## 5  76.2  76.3  76.5  76.6  76.8  77.0  77.1  77.3  77.4  77.6  77.7  77.8  78.0
## 6  78.8  78.9  79.1  79.3  79.4  79.6  79.8  79.9  80.1  80.3  80.4  80.6  80.7
##   X2045 X2046 X2047 X2048 X2049 X2050 X2051 X2052 X2053 X2054 X2055 X2056 X2057
## 1  69.2  69.4  69.5  69.7  69.8  70.0  70.2  70.3  70.5  70.6  70.8  70.9  71.1
## 2  69.7  69.9  70.0  70.2  70.3  70.5  70.6  70.7  70.9  71.0  71.2  71.3  71.4
## 3  83.2  83.3  83.5  83.6  83.8  83.9  84.0  84.2  84.3  84.5  84.6  84.7  84.9
## 4  85.8  85.9  86.0  86.1  86.3  86.4  86.5  86.6  86.7  86.8  87.0  87.1  87.2
## 5  78.1  78.3  78.4  78.5  78.7  78.8  78.9  79.0  79.2  79.3  79.4  79.5  79.7
## 6  80.9  81.0  81.2  81.4  81.5  81.7  81.8  82.0  82.1  82.2  82.4  82.5  82.7
##   X2058 X2059 X2060 X2061 X2062 X2063 X2064 X2065 X2066 X2067 X2068 X2069 X2070
## 1  71.2  71.3  71.5  71.6  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.8  72.9
## 2  71.6  71.7  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.7  72.9  73.0  73.1
## 3  85.0  85.1  85.2  85.4  85.5  85.6  85.7  85.9  86.0  86.1  86.2  86.3  86.5
## 4  87.3  87.4  87.5  87.7  87.8  87.9  88.0  88.1  88.2  88.3  88.5  88.6  88.7
## 5  79.8  79.9  80.0  80.2  80.3  80.4  80.5  80.6  80.8  80.9  81.0  81.1  81.2
## 6  82.8  82.9  83.1  83.2  83.3  83.5  83.6  83.7  83.8  84.0  84.1  84.2  84.3
##   X2071 X2072 X2073 X2074 X2075 X2076 X2077 X2078 X2079 X2080 X2081 X2082 X2083
## 1  73.0  73.2  73.3  73.5  73.6  73.8  73.9  74.1  74.2  74.3  74.5  74.6  74.8
## 2  73.3  73.4  73.5  73.6  73.8  73.9  74.0  74.1  74.3  74.4  74.5  74.6  74.8
## 3  86.6  86.7  86.8  86.9  87.1  87.2  87.3  87.4  87.5  87.7  87.8  87.9  88.0
## 4  88.8  88.9  89.0  89.1  89.2  89.3  89.5  89.6  89.7  89.8  89.9  90.0  90.1
## 5  81.4  81.5  81.6  81.7  81.8  82.0  82.1  82.2  82.3  82.4  82.5  82.6  82.8
## 6  84.5  84.6  84.7  84.8  84.9  85.1  85.2  85.3  85.4  85.5  85.6  85.8  85.9
##   X2084 X2085 X2086 X2087 X2088 X2089 X2090 X2091 X2092 X2093 X2094 X2095 X2096
## 1  74.9  75.1  75.2  75.4  75.5  75.6  75.8  75.9  76.1  76.2  76.4  76.5  76.7
## 2  74.9  75.0  75.1  75.3  75.4  75.5  75.6  75.8  75.9  76.0  76.1  76.3  76.4
## 3  88.1  88.2  88.4  88.5  88.6  88.7  88.8  88.9  89.0  89.2  89.3  89.4  89.5
## 4  90.2  90.3  90.5  90.6  90.7  90.8  90.9  91.0  91.1  91.3  91.4  91.5  91.6
## 5  82.9  83.0  83.1  83.2  83.3  83.4  83.5  83.7  83.8  83.9  84.0  84.1  84.2
## 6  86.0  86.1  86.2  86.3  86.5  86.6  86.7  86.8  86.9  87.0  87.2  87.3  87.4
##   X2097 X2098 X2099 X2100
## 1  76.8  77.0  77.1  77.3
## 2  76.5  76.7  76.8  76.9
## 3  89.6  89.7  89.8  90.0
## 4  91.7  91.8  91.9  92.0
## 5  84.3  84.5  84.6  84.7
## 6  87.5  87.6  87.7  87.8
# Check the column names
colnames(life_expectancy)
##   [1] "country" "X1800"   "X1801"   "X1802"   "X1803"   "X1804"   "X1805"  
##   [8] "X1806"   "X1807"   "X1808"   "X1809"   "X1810"   "X1811"   "X1812"  
##  [15] "X1813"   "X1814"   "X1815"   "X1816"   "X1817"   "X1818"   "X1819"  
##  [22] "X1820"   "X1821"   "X1822"   "X1823"   "X1824"   "X1825"   "X1826"  
##  [29] "X1827"   "X1828"   "X1829"   "X1830"   "X1831"   "X1832"   "X1833"  
##  [36] "X1834"   "X1835"   "X1836"   "X1837"   "X1838"   "X1839"   "X1840"  
##  [43] "X1841"   "X1842"   "X1843"   "X1844"   "X1845"   "X1846"   "X1847"  
##  [50] "X1848"   "X1849"   "X1850"   "X1851"   "X1852"   "X1853"   "X1854"  
##  [57] "X1855"   "X1856"   "X1857"   "X1858"   "X1859"   "X1860"   "X1861"  
##  [64] "X1862"   "X1863"   "X1864"   "X1865"   "X1866"   "X1867"   "X1868"  
##  [71] "X1869"   "X1870"   "X1871"   "X1872"   "X1873"   "X1874"   "X1875"  
##  [78] "X1876"   "X1877"   "X1878"   "X1879"   "X1880"   "X1881"   "X1882"  
##  [85] "X1883"   "X1884"   "X1885"   "X1886"   "X1887"   "X1888"   "X1889"  
##  [92] "X1890"   "X1891"   "X1892"   "X1893"   "X1894"   "X1895"   "X1896"  
##  [99] "X1897"   "X1898"   "X1899"   "X1900"   "X1901"   "X1902"   "X1903"  
## [106] "X1904"   "X1905"   "X1906"   "X1907"   "X1908"   "X1909"   "X1910"  
## [113] "X1911"   "X1912"   "X1913"   "X1914"   "X1915"   "X1916"   "X1917"  
## [120] "X1918"   "X1919"   "X1920"   "X1921"   "X1922"   "X1923"   "X1924"  
## [127] "X1925"   "X1926"   "X1927"   "X1928"   "X1929"   "X1930"   "X1931"  
## [134] "X1932"   "X1933"   "X1934"   "X1935"   "X1936"   "X1937"   "X1938"  
## [141] "X1939"   "X1940"   "X1941"   "X1942"   "X1943"   "X1944"   "X1945"  
## [148] "X1946"   "X1947"   "X1948"   "X1949"   "X1950"   "X1951"   "X1952"  
## [155] "X1953"   "X1954"   "X1955"   "X1956"   "X1957"   "X1958"   "X1959"  
## [162] "X1960"   "X1961"   "X1962"   "X1963"   "X1964"   "X1965"   "X1966"  
## [169] "X1967"   "X1968"   "X1969"   "X1970"   "X1971"   "X1972"   "X1973"  
## [176] "X1974"   "X1975"   "X1976"   "X1977"   "X1978"   "X1979"   "X1980"  
## [183] "X1981"   "X1982"   "X1983"   "X1984"   "X1985"   "X1986"   "X1987"  
## [190] "X1988"   "X1989"   "X1990"   "X1991"   "X1992"   "X1993"   "X1994"  
## [197] "X1995"   "X1996"   "X1997"   "X1998"   "X1999"   "X2000"   "X2001"  
## [204] "X2002"   "X2003"   "X2004"   "X2005"   "X2006"   "X2007"   "X2008"  
## [211] "X2009"   "X2010"   "X2011"   "X2012"   "X2013"   "X2014"   "X2015"  
## [218] "X2016"   "X2017"   "X2018"   "X2019"   "X2020"   "X2021"   "X2022"  
## [225] "X2023"   "X2024"   "X2025"   "X2026"   "X2027"   "X2028"   "X2029"  
## [232] "X2030"   "X2031"   "X2032"   "X2033"   "X2034"   "X2035"   "X2036"  
## [239] "X2037"   "X2038"   "X2039"   "X2040"   "X2041"   "X2042"   "X2043"  
## [246] "X2044"   "X2045"   "X2046"   "X2047"   "X2048"   "X2049"   "X2050"  
## [253] "X2051"   "X2052"   "X2053"   "X2054"   "X2055"   "X2056"   "X2057"  
## [260] "X2058"   "X2059"   "X2060"   "X2061"   "X2062"   "X2063"   "X2064"  
## [267] "X2065"   "X2066"   "X2067"   "X2068"   "X2069"   "X2070"   "X2071"  
## [274] "X2072"   "X2073"   "X2074"   "X2075"   "X2076"   "X2077"   "X2078"  
## [281] "X2079"   "X2080"   "X2081"   "X2082"   "X2083"   "X2084"   "X2085"  
## [288] "X2086"   "X2087"   "X2088"   "X2089"   "X2090"   "X2091"   "X2092"  
## [295] "X2093"   "X2094"   "X2095"   "X2096"   "X2097"   "X2098"   "X2099"  
## [302] "X2100"
# Check the structure of the data
str(life_expectancy)
## 'data.frame':    196 obs. of  302 variables:
##  $ country: chr  "Afghanistan" "Angola" "Albania" "Andorra" ...
##  $ X1800  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1801  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1802  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1803  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1804  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1805  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1806  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1807  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1808  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1809  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1810  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1811  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1812  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1813  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1814  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1815  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1816  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1817  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1818  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1819  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1820  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1821  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1822  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1823  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1824  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1825  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1826  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1827  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1828  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1829  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1830  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1831  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1832  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1833  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1834  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1835  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1836  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1837  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1838  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1839  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1840  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1841  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1842  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1843  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1844  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1845  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1846  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1847  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1848  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1849  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1850  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1851  : num  27.9 27.1 35.4 NA 30.8 33.2 33.9 33.5 34 34.4 ...
##  $ X1852  : num  28 27.2 35.4 NA 31 33.2 33.9 33.5 34 34.4 ...
##  $ X1853  : num  28.2 27.4 35.4 NA 31.1 33.2 33.8 33.5 34.1 34.4 ...
##  $ X1854  : num  28.3 27.5 35.3 NA 31.2 33.2 33.7 33.5 34.1 34.4 ...
##  $ X1855  : num  28.5 27.6 35.3 NA 31.3 33.3 33.6 33.5 34.1 34.4 ...
##  $ X1856  : num  28.6 27.8 35.3 NA 31.5 33.3 33.5 33.5 34.1 34.4 ...
##  $ X1857  : num  28.8 27.9 35.3 NA 31.6 33.3 33.5 33.5 34.1 34.4 ...
##  $ X1858  : num  28.9 28 35.3 NA 31.7 33.3 33.4 33.5 34.1 34.4 ...
##  $ X1859  : num  29.1 28.2 35.3 NA 31.9 33.3 33.3 33.5 34.1 34.4 ...
##  $ X1860  : num  29.2 28.3 35.3 NA 32 33.3 33.2 33.5 34.1 34.4 ...
##  $ X1861  : num  29.4 28.4 35.2 NA 32.1 33.3 33.1 33.5 34.1 34.4 ...
##  $ X1862  : num  29.5 28.6 35.2 NA 32.2 33.3 33.1 33.5 34.1 34.4 ...
##  $ X1863  : num  29.7 28.7 35.2 NA 32.4 33.3 33 33.5 34.1 34.4 ...
##  $ X1864  : num  29.8 28.8 35.2 NA 32.5 33.3 32.4 33.5 34.1 34.4 ...
##  $ X1865  : num  30 28.9 35.2 NA 32.6 33.3 31.8 33.5 34.1 34.4 ...
##  $ X1866  : num  30.1 29.1 35.2 NA 32.8 33.4 31.2 33.6 34.1 34.4 ...
##  $ X1867  : num  30.3 29.2 35.1 NA 32.9 33.4 30.7 33.6 34.1 34.4 ...
##  $ X1868  : num  30.4 29.3 35.1 NA 33 33.4 30.1 33.6 34.1 34.4 ...
##  $ X1869  : num  30.6 29.5 35.1 NA 33.1 33.4 30.1 33.6 34.1 34.4 ...
##  $ X1870  : num  30.7 29.6 35.1 NA 33.3 33.4 30 33.6 34.1 34.4 ...
##  $ X1871  : num  30.9 29.7 35.1 NA 33.4 33.4 30 33.6 34.6 34.4 ...
##  $ X1872  : num  31 29.9 35.1 NA 33.5 33.4 30 33.6 35.1 34.5 ...
##  $ X1873  : num  31.2 30 35.1 NA 33.6 33.4 29.9 33.6 35.7 34.5 ...
##  $ X1874  : num  31.3 30.1 35 NA 33.8 33.4 30.1 33.6 36.2 34.6 ...
##  $ X1875  : num  31.5 30.3 35 NA 33.9 33.4 30.2 33.6 36.8 34.7 ...
##  $ X1876  : num  31.6 30.4 35 NA 34 33.4 30.3 33.6 37.3 34.7 ...
##  $ X1877  : num  31.8 30.5 35 NA 34.1 33.4 30.4 33.6 37.8 34.8 ...
##  $ X1878  : num  31.9 30.6 35 NA 34.3 33.4 30.5 33.6 38.3 34.8 ...
##  $ X1879  : num  32.1 30.8 35 NA 34.4 33.4 30.6 33.6 38.9 34.9 ...
##  $ X1880  : num  32.3 30.9 35 NA 34.5 33.4 30.8 33.6 39.4 34.9 ...
##  $ X1881  : num  32.4 31 34.9 NA 34.7 33.3 30.9 33.6 39.9 35 ...
##  $ X1882  : num  32.5 31.2 34.9 NA 34.8 33.2 31 33.6 40.5 35.2 ...
##  $ X1883  : num  32.7 31.3 34.9 NA 34.9 33.1 31.1 33.6 41 35.5 ...
##  $ X1884  : num  32.9 31.4 34.9 NA 35 33 31.2 33.6 41.5 35.7 ...
##  $ X1885  : num  33 31.6 34.9 NA 35.2 32.9 31.3 33.6 42.1 35.9 ...
##  $ X1886  : num  33.1 31.7 34.9 NA 35.3 33.2 31.4 33.6 42.6 36.1 ...
##  $ X1887  : num  33.3 31.8 34.9 NA 35.4 33.5 31.5 33.6 43.1 36.4 ...
##  $ X1888  : num  33.4 31.9 34.8 NA 35.6 33.8 31.6 33.6 43.7 36.6 ...
##  $ X1889  : num  33.6 32.1 34.8 NA 35.7 34.1 31.7 33.6 44.2 36.8 ...
##  $ X1890  : num  33.7 32.2 34.8 NA 35.8 34.4 31.8 33.6 44.7 37 ...
##  $ X1891  : num  33.9 32.3 34.8 NA 36 34.2 31.9 33.6 45.3 37.3 ...
##  $ X1892  : num  34 32.5 34.8 NA 36.1 34.1 32 33.6 45.8 37.8 ...
##  $ X1893  : num  34.2 32.6 34.8 NA 36.2 34 32.1 33.6 46.3 38.2 ...
##  $ X1894  : num  34.3 32.7 34.8 NA 36.3 33.8 32.2 33.6 46.9 38.7 ...
##  $ X1895  : num  34.5 32.9 34.7 NA 36.5 33.7 32.3 33.6 47.4 39.2 ...
##  $ X1896  : num  34.6 33 34.7 NA 36.6 34.4 32.4 33.6 47.9 39.6 ...
##  $ X1897  : num  34.8 33.1 34.7 NA 36.7 35.1 32.5 33.6 48.5 40.1 ...
##   [list output truncated]
# View the first few rows of the data
head(life_expectancy)
##       country X1800 X1801 X1802 X1803 X1804 X1805 X1806 X1807 X1808 X1809 X1810
## 1 Afghanistan  28.2  28.2  28.2  28.2  28.2  28.2  28.1  28.1  28.1  28.1  28.1
## 2      Angola  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3     Albania  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4     Andorra    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5         UAE  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6   Argentina  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1811 X1812 X1813 X1814 X1815 X1816 X1817 X1818 X1819 X1820 X1821 X1822 X1823
## 1  28.1  28.1  28.1  28.1  28.1  28.1  28.0  28.0  28.0  28.0  28.0  28.0  28.0
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1824 X1825 X1826 X1827 X1828 X1829 X1830 X1831 X1832 X1833 X1834 X1835 X1836
## 1  28.0  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.9  27.8
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1837 X1838 X1839 X1840 X1841 X1842 X1843 X1844 X1845 X1846 X1847 X1848 X1849
## 1  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.8  27.7  27.7  27.7  27.7
## 2  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0  27.0
## 3  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4  35.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7  30.7
## 6  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2  33.2
##   X1850 X1851 X1852 X1853 X1854 X1855 X1856 X1857 X1858 X1859 X1860 X1861 X1862
## 1  27.7  27.9  28.0  28.2  28.3  28.5  28.6  28.8  28.9  29.1  29.2  29.4  29.5
## 2  27.0  27.1  27.2  27.4  27.5  27.6  27.8  27.9  28.0  28.2  28.3  28.4  28.6
## 3  35.4  35.4  35.4  35.4  35.3  35.3  35.3  35.3  35.3  35.3  35.3  35.2  35.2
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  30.7  30.8  31.0  31.1  31.2  31.3  31.5  31.6  31.7  31.9  32.0  32.1  32.2
## 6  33.2  33.2  33.2  33.2  33.2  33.3  33.3  33.3  33.3  33.3  33.3  33.3  33.3
##   X1863 X1864 X1865 X1866 X1867 X1868 X1869 X1870 X1871 X1872 X1873 X1874 X1875
## 1  29.7  29.8  30.0  30.1  30.3  30.4  30.6  30.7  30.9  31.0  31.2  31.3  31.5
## 2  28.7  28.8  28.9  29.1  29.2  29.3  29.5  29.6  29.7  29.9  30.0  30.1  30.3
## 3  35.2  35.2  35.2  35.2  35.1  35.1  35.1  35.1  35.1  35.1  35.1  35.0  35.0
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  32.4  32.5  32.6  32.8  32.9  33.0  33.1  33.3  33.4  33.5  33.6  33.8  33.9
## 6  33.3  33.3  33.3  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4  33.4
##   X1876 X1877 X1878 X1879 X1880 X1881 X1882 X1883 X1884 X1885 X1886 X1887 X1888
## 1  31.6  31.8  31.9  32.1  32.3  32.4  32.5  32.7  32.9  33.0  33.1  33.3  33.4
## 2  30.4  30.5  30.6  30.8  30.9  31.0  31.2  31.3  31.4  31.6  31.7  31.8  31.9
## 3  35.0  35.0  35.0  35.0  35.0  34.9  34.9  34.9  34.9  34.9  34.9  34.9  34.8
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  34.0  34.1  34.3  34.4  34.5  34.7  34.8  34.9  35.0  35.2  35.3  35.4  35.6
## 6  33.4  33.4  33.4  33.4  33.4  33.3  33.2  33.1  33.0  32.9  33.2  33.5  33.8
##   X1889 X1890 X1891 X1892 X1893 X1894 X1895 X1896 X1897 X1898 X1899 X1900 X1901
## 1  33.6  33.7  33.9  34.0  34.2  34.3  34.5  34.6  34.8  34.9  35.1  35.2  35.4
## 2  32.1  32.2  32.3  32.5  32.6  32.7  32.9  33.0  33.1  33.3  33.4  33.5  33.6
## 3  34.8  34.8  34.8  34.8  34.8  34.8  34.7  34.7  34.7  34.7  34.7  34.7  34.6
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  35.7  35.8  36.0  36.1  36.2  36.3  36.5  36.6  36.7  36.8  37.0  37.1  37.2
## 6  34.1  34.4  34.2  34.1  34.0  33.8  33.7  34.4  35.1  35.9  36.6  37.3  37.9
##   X1902 X1903 X1904 X1905 X1906 X1907 X1908 X1909 X1910 X1911 X1912 X1913 X1914
## 1  35.5  35.7  35.8  36.0  36.1  36.2  36.4  36.5  36.7  36.8  37.0  37.1  37.3
## 2  33.8  33.9  34.0  34.2  34.3  34.4  34.6  34.7  34.8  35.0  35.1  35.2  35.3
## 3  34.6  34.6  34.6  34.6  34.6  34.6  34.5  34.5  34.5  34.5  34.5  34.5  34.5
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  37.4  37.5  37.6  37.7  37.9  38.0  38.1  38.3  38.4  38.5  38.6  38.8  38.9
## 6  38.5  39.1  39.7  40.3  41.1  41.9  42.6  43.4  44.2  44.8  45.3  45.9  46.5
##   X1915 X1916 X1917 X1918 X1919 X1920 X1921 X1922 X1923 X1924 X1925 X1926 X1927
## 1  37.4  37.6  37.7  9.88  38.0  38.1  38.3  38.4  38.6  38.7  38.9  39.0  39.2
## 2  35.5  35.6  35.7 13.90  36.0  36.1  36.3  36.4  36.5  36.6  36.8  36.9  37.0
## 3  34.4  34.4  34.4 18.90  34.4  34.4  34.4  34.3  34.3  34.3  34.3  34.3  34.3
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  39.0  39.1  39.3 32.70  39.5  39.7  39.8  39.9  40.0  40.2  40.3  40.4  40.5
## 6  47.0  47.9  48.7 42.50  50.3  51.2  51.7  52.2  52.7  53.2  53.7  54.0  54.4
##   X1928 X1929 X1930 X1931 X1932 X1933 X1934 X1935 X1936 X1937 X1938 X1939 X1940
## 1  39.3  39.4  39.6  39.7  39.9  40.0  40.2  40.3  40.5  40.6  40.7  40.9  41.0
## 2  37.2  37.3  37.4  37.6  37.7  37.8  38.0  38.1  38.2  38.4  38.5  38.6  38.7
## 3  34.3  34.2  35.1  35.9  36.8  37.6  38.5  39.3  40.2  41.0  41.9  41.4  40.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA    NA
## 5  40.7  40.8  40.9  41.1  41.2  41.3  41.5  41.6  41.7  41.8  42.0  42.1  42.2
## 6  54.8  55.1  55.5  55.5  55.5  55.5  55.5  55.6  56.6  57.6  58.6  59.6  60.6
##   X1941 X1942 X1943 X1944 X1945 X1946 X1947 X1948 X1949 X1950 X1951 X1952 X1953
## 1  41.2  41.4  41.5  41.7  41.9  42.0  42.2  42.4  42.5  42.7  42.9  43.1  43.5
## 2  39.4  40.1  40.8  41.4  42.1  42.8  43.5  44.2  44.9  45.6  45.6  45.6  45.6
## 3  40.0  38.5  35.6  32.8  45.3  48.2  49.6  50.5  51.4  52.2  53.6  54.5  55.4
## 4    NA    NA    NA    NA    NA    NA    NA    NA    NA  74.6  74.7  74.8  75.0
## 5  42.3  42.4  42.5  42.6  42.7  45.8  49.0  52.1  55.3  58.4  58.5  58.6  58.7
## 6  61.2  61.8  62.5  63.1  63.7  63.6  63.5  63.5  63.4  63.3  63.5  64.2  64.1
##   X1954 X1955 X1956 X1957 X1958 X1959 X1960 X1961 X1962 X1963 X1964 X1965 X1966
## 1  43.3  43.9  44.1  44.3  44.5  44.7  45.0  45.3  45.5  45.7  45.9  46.1  46.3
## 2  45.6  45.5  45.7  45.8  45.9  46.1  46.3  44.8  45.0  45.2  45.4  45.6  45.8
## 3  56.1  56.3  58.0  59.3  61.0  61.7  62.5  63.3  63.3  63.8  64.4  64.8  65.5
## 4  75.1  75.2  75.3  75.4  75.5  75.6  75.7  75.8  75.9  76.0  76.2  76.3  76.4
## 5  58.8  58.9  58.8  59.3  59.6  59.7  60.3  60.8  61.3  61.6  62.1  62.6  63.0
## 6  64.7  64.5  65.2  65.2  65.4  65.4  65.3  65.7  65.8  65.8  65.8  66.1  66.6
##   X1967 X1968 X1969 X1970 X1971 X1972 X1973 X1974 X1975 X1976 X1977 X1978 X1979
## 1  46.5  46.7  46.9  47.1  47.3  47.3  47.3  47.4  47.5  47.7  47.9  46.4  44.7
## 2  46.0  46.2  46.4  46.6  46.8  47.0  47.2  47.4  47.5  47.5  47.7  47.8  48.0
## 3  66.1  66.5  67.1  67.8  68.3  68.8  69.3  69.8  70.2  70.7  71.1  71.7  71.3
## 4  76.5  76.7  76.8  77.0  77.1  77.2  77.4  77.5  77.7  77.8  78.0  78.1  78.2
## 5  63.4  63.8  64.2  64.0  64.9  65.1  65.4  65.7  66.0  66.3  66.6  67.0  67.3
## 6  66.5  66.0  65.9  66.1  66.9  67.3  67.7  67.9  68.0  67.0  67.7  69.0  69.8
##   X1980 X1981 X1982 X1983 X1984 X1985 X1986 X1987 X1988 X1989 X1990 X1991 X1992
## 1  43.7  44.3  44.1  42.3  39.9  42.0  43.3  45.9  48.5  52.7  53.8  53.8  54.2
## 2  48.1  48.2  48.2  48.2  48.4  48.6  48.6  48.6  48.6  49.4  49.7  50.3  50.3
## 3  71.3  71.3  71.4  71.2  71.4  71.9  72.3  72.2  72.4  72.5  72.8  72.6  73.2
## 4  78.3  78.4  78.5  78.5  78.6  78.7  78.8  78.8  78.9  79.0  79.0  79.1  79.2
## 5  67.6  68.0  68.1  67.9  68.4  68.5  68.5  68.5  68.5  68.6  68.7  68.7  68.8
## 6  70.2  70.3  70.9  70.7  70.8  71.7  72.0  72.1  72.1  72.3  72.5  72.7  72.8
##   X1993 X1994 X1995 X1996 X1997 X1998 X1999 X2000 X2001 X2002 X2003 X2004 X2005
## 1  54.4  53.9  54.3  54.7  54.5  53.3  54.7  54.7  54.8  55.5  56.5  57.1  57.6
## 2  49.0  50.3  51.2  51.7  51.6  50.6  51.9  52.8  53.4  54.5  55.1  55.5  56.4
## 3  73.8  74.6  74.6  74.5  72.9  74.8  75.1  75.4  76.0  75.9  75.6  75.8  76.2
## 4  79.3  79.5  79.8  80.0  80.2  80.4  80.6  80.8  80.9  81.1  81.2  81.3  81.4
## 5  68.8  68.7  68.8  68.9  69.0  69.2  69.2  69.1  69.2  69.4  69.3  69.1  69.2
## 6  73.0  73.4  73.4  73.5  73.6  73.7  73.8  74.2  74.3  74.3  74.4  74.9  75.3
##   X2006 X2007 X2008 X2009 X2010 X2011 X2012 X2013 X2014 X2015 X2016 X2017 X2018
## 1  58.0  58.5  59.2  59.9  60.5  61.0  61.4  61.9  61.9  61.9  62.0  62.9  62.7
## 2  57.0  58.0  58.8  59.5  60.2  60.8  61.4  62.1  63.0  63.5  63.9  64.2  64.6
## 3  76.9  77.5  77.6  78.0  78.1  78.1  78.2  78.3  78.2  78.1  78.2  78.3  78.4
## 4  81.5  81.7  81.8  81.8  81.8  81.9  81.9  82.0  82.0  82.0  82.1  82.1  82.1
## 5  69.5  70.0  70.4  70.6  70.8  71.0  71.2  71.6  73.0  73.2  73.4  73.5  73.7
## 6  75.4  75.3  75.7  75.8  75.9  76.0  76.2  76.3  76.5  76.5  76.2  76.3  76.5
##   X2019 X2020 X2021 X2022 X2023 X2024 X2025 X2026 X2027 X2028 X2029 X2030 X2031
## 1  63.3  62.3  61.8  62.6  64.0  64.8  65.1  65.4  65.6  65.9  66.1  66.3  66.6
## 2  65.1  64.9  64.2  64.5  65.9  66.1  66.3  66.5  66.7  66.9  67.0  67.2  67.4
## 3  78.5  76.2  75.7  76.1  77.3  79.5  79.7  79.9  80.1  80.3  80.5  80.6  80.8
## 4  82.2  78.3  79.6  82.7  82.9  83.0  83.2  83.3  83.5  83.6  83.8  83.9  84.0
## 5  73.9  73.2  73.0  73.4  74.6  74.8  74.9  75.1  75.3  75.5  75.7  75.8  76.0
## 6  76.6  75.2  74.7  75.4  77.3  77.4  77.6  77.8  77.9  78.1  78.3  78.4  78.6
##   X2032 X2033 X2034 X2035 X2036 X2037 X2038 X2039 X2040 X2041 X2042 X2043 X2044
## 1  66.8  67.0  67.2  67.4  67.6  67.8  68.0  68.2  68.3  68.5  68.7  68.9  69.0
## 2  67.6  67.8  68.0  68.1  68.3  68.4  68.6  68.8  68.9  69.1  69.3  69.4  69.6
## 3  81.0  81.2  81.4  81.5  81.7  81.9  82.1  82.2  82.4  82.6  82.7  82.9  83.0
## 4  84.1  84.3  84.4  84.5  84.7  84.8  84.9  85.0  85.2  85.3  85.4  85.5  85.7
## 5  76.2  76.3  76.5  76.6  76.8  77.0  77.1  77.3  77.4  77.6  77.7  77.8  78.0
## 6  78.8  78.9  79.1  79.3  79.4  79.6  79.8  79.9  80.1  80.3  80.4  80.6  80.7
##   X2045 X2046 X2047 X2048 X2049 X2050 X2051 X2052 X2053 X2054 X2055 X2056 X2057
## 1  69.2  69.4  69.5  69.7  69.8  70.0  70.2  70.3  70.5  70.6  70.8  70.9  71.1
## 2  69.7  69.9  70.0  70.2  70.3  70.5  70.6  70.7  70.9  71.0  71.2  71.3  71.4
## 3  83.2  83.3  83.5  83.6  83.8  83.9  84.0  84.2  84.3  84.5  84.6  84.7  84.9
## 4  85.8  85.9  86.0  86.1  86.3  86.4  86.5  86.6  86.7  86.8  87.0  87.1  87.2
## 5  78.1  78.3  78.4  78.5  78.7  78.8  78.9  79.0  79.2  79.3  79.4  79.5  79.7
## 6  80.9  81.0  81.2  81.4  81.5  81.7  81.8  82.0  82.1  82.2  82.4  82.5  82.7
##   X2058 X2059 X2060 X2061 X2062 X2063 X2064 X2065 X2066 X2067 X2068 X2069 X2070
## 1  71.2  71.3  71.5  71.6  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.8  72.9
## 2  71.6  71.7  71.8  71.9  72.1  72.2  72.3  72.5  72.6  72.7  72.9  73.0  73.1
## 3  85.0  85.1  85.2  85.4  85.5  85.6  85.7  85.9  86.0  86.1  86.2  86.3  86.5
## 4  87.3  87.4  87.5  87.7  87.8  87.9  88.0  88.1  88.2  88.3  88.5  88.6  88.7
## 5  79.8  79.9  80.0  80.2  80.3  80.4  80.5  80.6  80.8  80.9  81.0  81.1  81.2
## 6  82.8  82.9  83.1  83.2  83.3  83.5  83.6  83.7  83.8  84.0  84.1  84.2  84.3
##   X2071 X2072 X2073 X2074 X2075 X2076 X2077 X2078 X2079 X2080 X2081 X2082 X2083
## 1  73.0  73.2  73.3  73.5  73.6  73.8  73.9  74.1  74.2  74.3  74.5  74.6  74.8
## 2  73.3  73.4  73.5  73.6  73.8  73.9  74.0  74.1  74.3  74.4  74.5  74.6  74.8
## 3  86.6  86.7  86.8  86.9  87.1  87.2  87.3  87.4  87.5  87.7  87.8  87.9  88.0
## 4  88.8  88.9  89.0  89.1  89.2  89.3  89.5  89.6  89.7  89.8  89.9  90.0  90.1
## 5  81.4  81.5  81.6  81.7  81.8  82.0  82.1  82.2  82.3  82.4  82.5  82.6  82.8
## 6  84.5  84.6  84.7  84.8  84.9  85.1  85.2  85.3  85.4  85.5  85.6  85.8  85.9
##   X2084 X2085 X2086 X2087 X2088 X2089 X2090 X2091 X2092 X2093 X2094 X2095 X2096
## 1  74.9  75.1  75.2  75.4  75.5  75.6  75.8  75.9  76.1  76.2  76.4  76.5  76.7
## 2  74.9  75.0  75.1  75.3  75.4  75.5  75.6  75.8  75.9  76.0  76.1  76.3  76.4
## 3  88.1  88.2  88.4  88.5  88.6  88.7  88.8  88.9  89.0  89.2  89.3  89.4  89.5
## 4  90.2  90.3  90.5  90.6  90.7  90.8  90.9  91.0  91.1  91.3  91.4  91.5  91.6
## 5  82.9  83.0  83.1  83.2  83.3  83.4  83.5  83.7  83.8  83.9  84.0  84.1  84.2
## 6  86.0  86.1  86.2  86.3  86.5  86.6  86.7  86.8  86.9  87.0  87.2  87.3  87.4
##   X2097 X2098 X2099 X2100
## 1  76.8  77.0  77.1  77.3
## 2  76.5  76.7  76.8  76.9
## 3  89.6  89.7  89.8  90.0
## 4  91.7  91.8  91.9  92.0
## 5  84.3  84.5  84.6  84.7
## 6  87.5  87.6  87.7  87.8
# Check the column names
colnames(life_expectancy)
##   [1] "country" "X1800"   "X1801"   "X1802"   "X1803"   "X1804"   "X1805"  
##   [8] "X1806"   "X1807"   "X1808"   "X1809"   "X1810"   "X1811"   "X1812"  
##  [15] "X1813"   "X1814"   "X1815"   "X1816"   "X1817"   "X1818"   "X1819"  
##  [22] "X1820"   "X1821"   "X1822"   "X1823"   "X1824"   "X1825"   "X1826"  
##  [29] "X1827"   "X1828"   "X1829"   "X1830"   "X1831"   "X1832"   "X1833"  
##  [36] "X1834"   "X1835"   "X1836"   "X1837"   "X1838"   "X1839"   "X1840"  
##  [43] "X1841"   "X1842"   "X1843"   "X1844"   "X1845"   "X1846"   "X1847"  
##  [50] "X1848"   "X1849"   "X1850"   "X1851"   "X1852"   "X1853"   "X1854"  
##  [57] "X1855"   "X1856"   "X1857"   "X1858"   "X1859"   "X1860"   "X1861"  
##  [64] "X1862"   "X1863"   "X1864"   "X1865"   "X1866"   "X1867"   "X1868"  
##  [71] "X1869"   "X1870"   "X1871"   "X1872"   "X1873"   "X1874"   "X1875"  
##  [78] "X1876"   "X1877"   "X1878"   "X1879"   "X1880"   "X1881"   "X1882"  
##  [85] "X1883"   "X1884"   "X1885"   "X1886"   "X1887"   "X1888"   "X1889"  
##  [92] "X1890"   "X1891"   "X1892"   "X1893"   "X1894"   "X1895"   "X1896"  
##  [99] "X1897"   "X1898"   "X1899"   "X1900"   "X1901"   "X1902"   "X1903"  
## [106] "X1904"   "X1905"   "X1906"   "X1907"   "X1908"   "X1909"   "X1910"  
## [113] "X1911"   "X1912"   "X1913"   "X1914"   "X1915"   "X1916"   "X1917"  
## [120] "X1918"   "X1919"   "X1920"   "X1921"   "X1922"   "X1923"   "X1924"  
## [127] "X1925"   "X1926"   "X1927"   "X1928"   "X1929"   "X1930"   "X1931"  
## [134] "X1932"   "X1933"   "X1934"   "X1935"   "X1936"   "X1937"   "X1938"  
## [141] "X1939"   "X1940"   "X1941"   "X1942"   "X1943"   "X1944"   "X1945"  
## [148] "X1946"   "X1947"   "X1948"   "X1949"   "X1950"   "X1951"   "X1952"  
## [155] "X1953"   "X1954"   "X1955"   "X1956"   "X1957"   "X1958"   "X1959"  
## [162] "X1960"   "X1961"   "X1962"   "X1963"   "X1964"   "X1965"   "X1966"  
## [169] "X1967"   "X1968"   "X1969"   "X1970"   "X1971"   "X1972"   "X1973"  
## [176] "X1974"   "X1975"   "X1976"   "X1977"   "X1978"   "X1979"   "X1980"  
## [183] "X1981"   "X1982"   "X1983"   "X1984"   "X1985"   "X1986"   "X1987"  
## [190] "X1988"   "X1989"   "X1990"   "X1991"   "X1992"   "X1993"   "X1994"  
## [197] "X1995"   "X1996"   "X1997"   "X1998"   "X1999"   "X2000"   "X2001"  
## [204] "X2002"   "X2003"   "X2004"   "X2005"   "X2006"   "X2007"   "X2008"  
## [211] "X2009"   "X2010"   "X2011"   "X2012"   "X2013"   "X2014"   "X2015"  
## [218] "X2016"   "X2017"   "X2018"   "X2019"   "X2020"   "X2021"   "X2022"  
## [225] "X2023"   "X2024"   "X2025"   "X2026"   "X2027"   "X2028"   "X2029"  
## [232] "X2030"   "X2031"   "X2032"   "X2033"   "X2034"   "X2035"   "X2036"  
## [239] "X2037"   "X2038"   "X2039"   "X2040"   "X2041"   "X2042"   "X2043"  
## [246] "X2044"   "X2045"   "X2046"   "X2047"   "X2048"   "X2049"   "X2050"  
## [253] "X2051"   "X2052"   "X2053"   "X2054"   "X2055"   "X2056"   "X2057"  
## [260] "X2058"   "X2059"   "X2060"   "X2061"   "X2062"   "X2063"   "X2064"  
## [267] "X2065"   "X2066"   "X2067"   "X2068"   "X2069"   "X2070"   "X2071"  
## [274] "X2072"   "X2073"   "X2074"   "X2075"   "X2076"   "X2077"   "X2078"  
## [281] "X2079"   "X2080"   "X2081"   "X2082"   "X2083"   "X2084"   "X2085"  
## [288] "X2086"   "X2087"   "X2088"   "X2089"   "X2090"   "X2091"   "X2092"  
## [295] "X2093"   "X2094"   "X2095"   "X2096"   "X2097"   "X2098"   "X2099"  
## [302] "X2100"
# Check the structure of the data
str(life_expectancy)
## 'data.frame':    196 obs. of  302 variables:
##  $ country: chr  "Afghanistan" "Angola" "Albania" "Andorra" ...
##  $ X1800  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1801  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1802  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1803  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1804  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1805  : num  28.2 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1806  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1807  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1808  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1809  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1810  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1811  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1812  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1813  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1814  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1815  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1816  : num  28.1 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1817  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1818  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1819  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1820  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1821  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1822  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1823  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1824  : num  28 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1825  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1826  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1827  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1828  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1829  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1830  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1831  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1832  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1833  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1834  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1835  : num  27.9 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1836  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1837  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1838  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1839  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1840  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1841  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1842  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1843  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1844  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1845  : num  27.8 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1846  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1847  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1848  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1849  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1850  : num  27.7 27 35.4 NA 30.7 33.2 34 33.5 34 34.4 ...
##  $ X1851  : num  27.9 27.1 35.4 NA 30.8 33.2 33.9 33.5 34 34.4 ...
##  $ X1852  : num  28 27.2 35.4 NA 31 33.2 33.9 33.5 34 34.4 ...
##  $ X1853  : num  28.2 27.4 35.4 NA 31.1 33.2 33.8 33.5 34.1 34.4 ...
##  $ X1854  : num  28.3 27.5 35.3 NA 31.2 33.2 33.7 33.5 34.1 34.4 ...
##  $ X1855  : num  28.5 27.6 35.3 NA 31.3 33.3 33.6 33.5 34.1 34.4 ...
##  $ X1856  : num  28.6 27.8 35.3 NA 31.5 33.3 33.5 33.5 34.1 34.4 ...
##  $ X1857  : num  28.8 27.9 35.3 NA 31.6 33.3 33.5 33.5 34.1 34.4 ...
##  $ X1858  : num  28.9 28 35.3 NA 31.7 33.3 33.4 33.5 34.1 34.4 ...
##  $ X1859  : num  29.1 28.2 35.3 NA 31.9 33.3 33.3 33.5 34.1 34.4 ...
##  $ X1860  : num  29.2 28.3 35.3 NA 32 33.3 33.2 33.5 34.1 34.4 ...
##  $ X1861  : num  29.4 28.4 35.2 NA 32.1 33.3 33.1 33.5 34.1 34.4 ...
##  $ X1862  : num  29.5 28.6 35.2 NA 32.2 33.3 33.1 33.5 34.1 34.4 ...
##  $ X1863  : num  29.7 28.7 35.2 NA 32.4 33.3 33 33.5 34.1 34.4 ...
##  $ X1864  : num  29.8 28.8 35.2 NA 32.5 33.3 32.4 33.5 34.1 34.4 ...
##  $ X1865  : num  30 28.9 35.2 NA 32.6 33.3 31.8 33.5 34.1 34.4 ...
##  $ X1866  : num  30.1 29.1 35.2 NA 32.8 33.4 31.2 33.6 34.1 34.4 ...
##  $ X1867  : num  30.3 29.2 35.1 NA 32.9 33.4 30.7 33.6 34.1 34.4 ...
##  $ X1868  : num  30.4 29.3 35.1 NA 33 33.4 30.1 33.6 34.1 34.4 ...
##  $ X1869  : num  30.6 29.5 35.1 NA 33.1 33.4 30.1 33.6 34.1 34.4 ...
##  $ X1870  : num  30.7 29.6 35.1 NA 33.3 33.4 30 33.6 34.1 34.4 ...
##  $ X1871  : num  30.9 29.7 35.1 NA 33.4 33.4 30 33.6 34.6 34.4 ...
##  $ X1872  : num  31 29.9 35.1 NA 33.5 33.4 30 33.6 35.1 34.5 ...
##  $ X1873  : num  31.2 30 35.1 NA 33.6 33.4 29.9 33.6 35.7 34.5 ...
##  $ X1874  : num  31.3 30.1 35 NA 33.8 33.4 30.1 33.6 36.2 34.6 ...
##  $ X1875  : num  31.5 30.3 35 NA 33.9 33.4 30.2 33.6 36.8 34.7 ...
##  $ X1876  : num  31.6 30.4 35 NA 34 33.4 30.3 33.6 37.3 34.7 ...
##  $ X1877  : num  31.8 30.5 35 NA 34.1 33.4 30.4 33.6 37.8 34.8 ...
##  $ X1878  : num  31.9 30.6 35 NA 34.3 33.4 30.5 33.6 38.3 34.8 ...
##  $ X1879  : num  32.1 30.8 35 NA 34.4 33.4 30.6 33.6 38.9 34.9 ...
##  $ X1880  : num  32.3 30.9 35 NA 34.5 33.4 30.8 33.6 39.4 34.9 ...
##  $ X1881  : num  32.4 31 34.9 NA 34.7 33.3 30.9 33.6 39.9 35 ...
##  $ X1882  : num  32.5 31.2 34.9 NA 34.8 33.2 31 33.6 40.5 35.2 ...
##  $ X1883  : num  32.7 31.3 34.9 NA 34.9 33.1 31.1 33.6 41 35.5 ...
##  $ X1884  : num  32.9 31.4 34.9 NA 35 33 31.2 33.6 41.5 35.7 ...
##  $ X1885  : num  33 31.6 34.9 NA 35.2 32.9 31.3 33.6 42.1 35.9 ...
##  $ X1886  : num  33.1 31.7 34.9 NA 35.3 33.2 31.4 33.6 42.6 36.1 ...
##  $ X1887  : num  33.3 31.8 34.9 NA 35.4 33.5 31.5 33.6 43.1 36.4 ...
##  $ X1888  : num  33.4 31.9 34.8 NA 35.6 33.8 31.6 33.6 43.7 36.6 ...
##  $ X1889  : num  33.6 32.1 34.8 NA 35.7 34.1 31.7 33.6 44.2 36.8 ...
##  $ X1890  : num  33.7 32.2 34.8 NA 35.8 34.4 31.8 33.6 44.7 37 ...
##  $ X1891  : num  33.9 32.3 34.8 NA 36 34.2 31.9 33.6 45.3 37.3 ...
##  $ X1892  : num  34 32.5 34.8 NA 36.1 34.1 32 33.6 45.8 37.8 ...
##  $ X1893  : num  34.2 32.6 34.8 NA 36.2 34 32.1 33.6 46.3 38.2 ...
##  $ X1894  : num  34.3 32.7 34.8 NA 36.3 33.8 32.2 33.6 46.9 38.7 ...
##  $ X1895  : num  34.5 32.9 34.7 NA 36.5 33.7 32.3 33.6 47.4 39.2 ...
##  $ X1896  : num  34.6 33 34.7 NA 36.6 34.4 32.4 33.6 47.9 39.6 ...
##  $ X1897  : num  34.8 33.1 34.7 NA 36.7 35.1 32.5 33.6 48.5 40.1 ...
##   [list output truncated]

#I encountered a problem, all years are numbered as x1800 etc so I have to remove the x somehow

#The following code reformats the data, only preserving two columns, year and lifexpectancy. So we lose the data of gdp etc since it is now in a “long” format instead of “wide”.

# Reshape the data from wide to long format
life_expectancy_long <- life_expectancy %>%
  pivot_longer(
    cols = starts_with("X"),  # Select all columns starting with "X" (years)
    names_to = "year",        # Create a new column called "year"
    values_to = "life_expectancy"  # Store the life expectancy values
  )

# View the reshaped data
head(life_expectancy_long)
## # A tibble: 6 × 3
##   country     year  life_expectancy
##   <chr>       <chr>           <dbl>
## 1 Afghanistan X1800            28.2
## 2 Afghanistan X1801            28.2
## 3 Afghanistan X1802            28.2
## 4 Afghanistan X1803            28.2
## 5 Afghanistan X1804            28.2
## 6 Afghanistan X1805            28.2

#Now I remove the “X” that had been preventing me from using the original dataset. The “x” makes Rstudio recognise the column as charecters which prevents me from analysing.

# Remove the "X" prefix and convert the year column to numeric
life_expectancy_long <- life_expectancy_long %>%
  mutate(year = as.numeric(sub("X", "", year)))

# View the cleaned data
head(life_expectancy_long)
## # A tibble: 6 × 3
##   country      year life_expectancy
##   <chr>       <dbl>           <dbl>
## 1 Afghanistan  1800            28.2
## 2 Afghanistan  1801            28.2
## 3 Afghanistan  1802            28.2
## 4 Afghanistan  1803            28.2
## 5 Afghanistan  1804            28.2
## 6 Afghanistan  1805            28.2

#I am only interested in the data from 2000, the year I was born, to 2025 current year.

# Filter the data for 2000 to 2025
life_expectancy_2000_2025 <- life_expectancy_long %>% filter(year >= 2000 & year <= 2025)

# View the filtered data
head(life_expectancy_2000_2025)
## # A tibble: 6 × 3
##   country      year life_expectancy
##   <chr>       <dbl>           <dbl>
## 1 Afghanistan  2000            54.7
## 2 Afghanistan  2001            54.8
## 3 Afghanistan  2002            55.5
## 4 Afghanistan  2003            56.5
## 5 Afghanistan  2004            57.1
## 6 Afghanistan  2005            57.6

#Next we calculate the average lifespan of the global population from 2000 to 2025, as can be seen after running the code below, the global average lifespan is steadily increasing. There are some minor hicups though I wonder if a certain global pandemic had anything to do with the decline from 2019 to 2021.

# Calculate average life expectancy for each year from 2000 to 2025
avg_life_exp <- life_expectancy_2000_2025 %>%
  group_by(year) %>%
  summarize(avg_life_exp = mean(life_expectancy, na.rm = TRUE))  # Remove NA values

# View the result
avg_life_exp
## # A tibble: 26 × 2
##     year avg_life_exp
##    <dbl>        <dbl>
##  1  2000         67.5
##  2  2001         67.8
##  3  2002         68.0
##  4  2003         68.3
##  5  2004         68.5
##  6  2005         68.9
##  7  2006         69.2
##  8  2007         69.6
##  9  2008         69.9
## 10  2009         70.3
## # ℹ 16 more rows

#Time to put an

# Line plot of average life expectancy from 2000 to 2025
ggplot(avg_life_exp, aes(x = year, y = avg_life_exp)) +
  geom_line(color = "blue", size = 1) +  # Add a blue line
  geom_point(color = "red", size = 3) +  # Add red points for each year
  labs(
    title = "Trend in Average Life Expectancy (2000-2025)",
    x = "Year",
    y = "Average Life Expectancy (years)"
  ) +
  theme_minimal() +
  scale_x_continuous(breaks = seq(2000, 2025, by = 5))  # Add x-axis labels every 5 years
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

#Seems like we have just barely reached pre corona levels this year.

#below is the code I used to save the image to put into word

# Create the plot
plot <- ggplot(avg_life_exp, aes(x = year, y = avg_life_exp)) +
  geom_line(color = "blue", size = 1) +  # Add a blue line
  geom_point(color = "red", size = 3) +  # Add red points for each year
  labs(
    title = "Trend in Average Life Expectancy (2000-2025)",
    x = "Year",
    y = "Average Life Expectancy (years)"
  ) +
  theme_minimal() +
  scale_x_continuous(breaks = seq(2000, 2025, by = 5))  # Add x-axis labels every 5 years

# Print the plot to confirm it's created correctly
print(plot)

# Save the plot as a PNG file
ggsave("life_expectancy_2000_2025.png", plot, width = 10, height = 6, dpi = 300)